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Sahlgren and A. Holst and P. Kanerva}, + year = 2008, + title = {Permutations as a Means to Encode Order in Word Space}, + booktitle = {Proceedings of the 30th Annual Meeting of the Cognitive Science Society (CogSci'08)}, + location = {Washington D.C., USA}, +} + +@article{salton75vector, + author = {G. Salton and A. Wong and and C. S. Yang}, + year = 1975, + title = {A Vector Space Model for Automatic Indexing}, + journal = {Communications of the ACM}, + volume = 18, + number = 11, + pages = {613-–620}, +} + +@article{schutze97cooccurrence, + address = {Tarrytown, NY, USA}, + author = {Sch\"{u}tze, Hinrich and Pedersen, Jan O. }, + journal = {Information Processing and Management}, + number = {3}, + pages = {307--318}, + publisher = {Pergamon Press, Inc.}, + title = {A cooccurrence-based thesaurus and two applications to information retrieval}, + volume = {33}, + year = {1997} +} + +@inproceedings{sia08efficient, + author = {Ka Cheung Sia and Junghoo Cho and Yun Chi and Belle L. Tseng}, + title = {Efficient Computation of Personal Aggregate Queries on Blogs}, + booktitle = {Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD)}, + month = {August}, + year = 2008, +} + +@techreport{vinokourov2002finding, + author = {Vinokourov, A. and Shawe-Taylor, J. and Cristianini, N.}, + title = {Finding {L}anguage-{I}ndependent {S}emantic {R}epresentation of {T}ext + using {K}ernel {C}anonical {C}orrelation {A}nalysis}, + institution = {Neurocolt}, + year = {2002}, + note = {NeuroCOLT Technical Report NC-TR-02-119}, +} diff --git a/papers/2009_ranlp_ettt_temporal_random_indexing/cml_paper.tex b/papers/2009_ranlp_ettt_temporal_random_indexing/cml_paper.tex new file mode 100644 index 00000000..d0cca998 --- /dev/null +++ b/papers/2009_ranlp_ettt_temporal_random_indexing/cml_paper.tex @@ -0,0 +1,859 @@ +\documentclass[a4paper,twocolumn,twoside,10pt]{ranlp} +\usepackage{epsfig} +\usepackage{latexsym} +\usepackage[usenames]{color} +\usepackage{times} +\usepackage{verbatim} +\usepackage{multirow} + +\begin{document} +\title{Event Detection in Blogs using Temporal Random Indexing} + + +\author{ {\bf David Jurgens} and {\bf Keith Stevens} \\ +University of California, Los Angeles \\ +4732 Boelter Hall \\ +Los Angeles, CA 90095 \\ +\email{\{jurgens,\ kstevens\}}{cs.ucla.edu} \\ +} + +\date{} + +\maketitle + +\thispagestyle{empty} \pagestyle{empty} + +\begin{abstract} + +Automatic event detection aims to identify novel, interesting topics as they are +published online. While existing algorithms for event detection have focused on +newswire releases, we examine how event detection can work on less structured +corpora of blogs. +% +The proliferation of blogs and other forms of self-published media have given +rise to an ever-growing corpus of news, commentary and opinion texts. +% +Blogs offer a major advantage for event detection as their content may be +rapidly updated. However, blogs texts also pose a significant challenge in that +the described events may be less easy to detect given the variety of topics, writing +styles and possible author biases. +% +We propose a new way of detecting events in this media by looking for changes in +word semantics. +% +We first outline a new algorithm that makes use of a temporally-annotated +semantic space for tracking how words change semantics. +% +Then we demonstrate how identified changes could be used to detect new events +and their associated blog entries. + +\end{abstract} + +\section {Introduction} + +Automated event detection is a form of information retrieval where given a +time-ordered set of documents, an algorithm must select those which represent +recent news or changes to existing information. An automated approach to event +detection has many practical applications; given the large amount of text being +written daily, readers want to be informed of which developments and topics are +the most recent and important without having to manually sift through all the +documents written on the topic. In addition, a robust system should be able to +detect multiple kinds of events, such as international conflicts, product +releases or sports results. The main challenge in automating this task is +detecting what makes a new document sufficiently novel to be described as a new +event. + +Current event detection approaches have focused on identifying concrete events +that occur within newswire text\cite{kumaran04entityevent}. However, in recent +years, blogs have become an important source of both news and commentary. Unlike +news reports, blog content expresses a wide range of topics, opinions, +vocabulary and writing styles; the change in editorial requirements allows blog +authors to comment freely on local, national and international issues, while +still expressing their personal sentiment. Accordingly, blogs offer a rich +opportunity for detecting events that may not be covered in traditional newswire +text. These forms of self published media might also allow event detection +systems to identify developing events before official news reports can be written. + +Several forms of event detection have focused on analyzing named entities, such +as ``Bill Clinton'' or ``Iraq,'' and the contexts or documents in which they +appear, e.g. +\cite{kontostathis04use,kumaran04entityevent,fortuna09visualization}. We +propose a more general approach that looks at all words and their contexts, +rather than a predetermined set of words. Specifically, we argue that event +detection can be done by measuring the semantic change in a word or phrase. To +track changes in the semantics, we use a semantic space model of meaning, which +is an automated method of building distributed representations of word meaning. + +Semantic space models of meaning offer three notable advantages for event +detection. +% +First, the models are capable of automatically determining the semantics of a +word by examining the contexts in which the word appears. Such automated +understanding of semantics is required for analyzing these new sources of data +due to the much wider vocabulary used by authors. +% +Second, the models offer a well defined method for comparing the semantics +between words. These semantic comparisons have been shown to be similar to +human judgments\cite{landauer97solution}. We argue that reporting words which +have a notable changes in semantics should correlate well with a reader's +expectations of interesting developments. +% +Third, the models are well-established at detecting association such as synonymy +among words, which can allow models to detect events that are referred to by +multiple names. +% +Given these advantages, we introduce a new semantic space algorithm for +assessing how the meaning of a word changes through time for the purpose of +event detection. + +We illustrate our approach to topic detection with a hypothetical example of the +product release of a toy named ``blick.'' At the start of the toy's popularity, +the word ``blick'' has not occurred before and therefore its semantics would be +undefined. +% +As ``blick'' appears in more blogs, the word acquires consistent semantics, and +the algorithm can report a new event for ``blick.'' Our approach differs from +simple occurrence monitoring in that we require the word to have a consistent +meaning; unless the algorithm is capable of determining what concepts the word +refers to, knowing that the word relates to an event is impossible. + +However, consider detecting a second event for ``blick'' soon after its release +in which the toy is discovered to have toxic properties. Since the toy's name +was already present in the blogs, the novelty of the name is not enough to +detect the point at which the toxic chemical was revealed. However, our +approach, which looks at the semantic shift of words over time, would detect a +shift based on the new kinds of words that would be likely to co-occur with the +toy's name, e.g. toxicity, a toy recall, or lawsuit. Intuitively speaking, this +approach associates news events with noticeable changes in both \emph{what} +authors talk about and \emph{how} they talk about those subject. + +In this paper we present a new algorithm, Temporal Random Indexing, that +effectively captures the semantic changes for words and phrases over time. We +first briefly review the semantic space model that underlies this approach and +then present the algorithm. Following, we demonstrate several examples of +semantic change extracted from a large blog corpus and illustrate one method for +reporting the events. + +\section {Semantic Space Models} + +Semantic space models of meaning are born from the distributed hypothesis: For +two words, their similarity in meaning is predicted by the similarity of their +distributions of co-occurring words\cite{harris68mathematical}, or as Firth puts +it, ``you shall know a word by the company it keeps,''\cite{firth57synopsis}. +Creating semantics from co-occurring words forms the basis for how our algorithm +represents changes in semantics. + +\subsection{Semantics as Co-occurrence} + +In a semantic space, a word's semantics are mapped to high dimensional vectors +in a geometric space. The dimensions of the space represent distinctions +between the meanings of words; accordingly, words with similar semantics have +similar vector representations. Semantic space representations have proven +effective at a variety of information retrieval tasks such as identifying +synonymous queries\cite{schutze97cooccurrence} and multi-language +retrieval\cite{littman98automatic,vinokourov2002finding}. For a recent survey +of applications of semantic spaces to information retrieval see Cohen and +Widdows\cite{cohen09empirical}. To illustrate the basics of co-occurrence based +semantic space models, we can further explore the example of ``blick'', the new +yet toxic toy. + +Consider the documents describing ``blick'' when it is first introduced during a +holiday season. A potential line from several blogs might read ``A perfect gift +this holiday season is blick, one of the newest toys available!'' Using a +simple co-occurrence semantic space, the semantics of ``blick'' would be a count +of how frequently it co-occurs with key words such as: gift, holiday, perfect +and toys. Examining later blog posts written when this same toy is discovered +to have toxic elements, several posts might now have the line: ``the toxic +elements in blick make the toy dangerous.'' The semantics of the toy should now +focus primarily on the co-occurrence of words such as toxic and dangerous, and +should no longer be associated with positive words such as holiday and perfect. +Figure \ref{fig:ri-space} illustrates a simplified two-dimensional semantic +space and the changes to semantics that would occur as ``blick'' begins to +co-occur with toxic-related words. A standard semantic space model would define +the semantics of the new toy as a combination of all co-occurrences, in this +case the positive new semantics and the negative semantics of toxicity. + +\subsection{Random Indexing} + +Using simple co-occurrence is rarely done in practice for large corpora. In +such models, each unique word would be assigned its own dimension (corresponding +to co-occurrence with that word), which results in vectors with hundreds of +thousands to millions of dimensions. Basing the number of dimensions on the +number of unique words is particularly problematic for blog corpora, as writers +frequently introduce misspellings, slang, or topic-specific jargon. +Accordingly, many approaches have focused on reducing the dimensionality of the +semantic space. Dimensionality reduction often has the additional benefits such +as making the resulting vector more general, or reducing computation time. + +Early successful approaches such as Latent Semantic +Analysis\cite{landauer97solution} use the Singular Value Decomposition (SVD) to +reduce the number of dimensions. While the SVD results in significant +improvements in information retrieval, the fastest algorithms for the SVD are +O(mn$^2$) \cite{bau97numlinalg}, which make them impractical for large corpora. +Moreover, the SVD and other forms of principle component analysis must have the +entire corpus present at once, which makes it difficult to update the space as +new words and contexts are added. This is particularly problematic for event +detection, as the corpus is expected to continuously grow as new events occur. + +Random Indexing\cite{kanerva00random,sahlgren01vector} offers an alternative +method for reducing the dimensionality of the semantic space by using a random +projection of the full co-occurrence matrix onto a lower dimensional space. +Random Indexing operates as follows. Each unique word is assigned an +\emph{index vector}, which is a random, sparse vector in a high dimensional +space, often 2000-10000 dimensions. The size of the index vectors sets the +number of dimensions used in the resulting semantic space. Index vectors are +created such that any two arbitrary index vectors have a high probability of +being orthogonal. This property is necessary to accurately approximate the +original word co-occurrence matrix in a lower dimension. The semantics of each +word are calculated by summing the index vectors of all co-occurring words +within a small window of text. Random Indexing works well in practice as the +dimensionality reduction occurs as the corpus is being processed, rather than +requiring an explicit step after all the corpus has been seen. + +More formally, let $w$ be a focus word, $w_i$ be a co-occurring word with a word +distance of $i$ and $index(w_i)$ be the co-occurring word's index vector. For +the current word, we define a window of size $n$ words before and after, which +are counted as co-occurring. The semantics of $w$ are then defined as: +% +\begin{equation} +\label{eq:random_indexing} +semantics(w) = \sum_{\forall c \in D} \sum_{ -n \leq i \leq n} index(w_i) +\end{equation} +% +where $c$ is each occurrence of $w$ in the corpus $D$. + + +\begin{figure} + \center + \includegraphics[width=.35\textwidth]{figures/example-semantic-space.eps} + \caption{Word semantics projected into two dimensions, illustrating the + hypothetical change in meaning for ``blick'' based on its nearest neighbors} + \label{fig:ri-space} +\end{figure} + +\subsection{Adding Time to Semantic Space Models} + +Augmenting a semantic space with time has been recognized as an effective method +for tracking changes in semantics\cite{sahlgren08buzz}. Two methods have been + used to add temporal semantics. The first approach builds a separate semantic + space for each specific time range. Semantics are then compared across spaces + by defining some common context which occurs in both spaces. The second + approach builds a single semantic space but provides the ability to segment it + based on time. The key difference between these approaches lies in the + meaning of each semantic dimension; when multiple spaces are used, there is no + guarantee that the specific semantic meaning associated with some dimension + $i$ will be the same for dimension $i$ in another space. + +Kontostathis et al.\cite{kontostathis04use} and Fortuna et +al.\cite{fortuna09visualization} have independently proposed two successful +semantic space algorithms that use the first approach of processing several +distinct corpora. Both approaches collect several corpora which span unique +time ranges, and construct a semantic space for each corpus using LSA. Using +LSA is a notable challenge as the space defined by LSA is based on the SVD of a +word $\times$ document matrix; with documents being unique to each time-span's +corpus, direct comparison of vectors between spaces is not feasible. + +Kontostathis et al.\cite{kontostathis04use} use data mining to overcome the +change in dimension-meaning by first clustering the semantics from each year. +With this clustering, key attributes are extracted from several time ranges, and +significant differences are used to infer an event or trend. In essence, vector +comparisons between the semantic spaces are bypassed by using cross-space +meta-statistics for each word generated from each space. This approach is +limited to being an offline approach due to the costly machine learning +techniques, and is further limited by key sets of attributes. + +Another approach for comparing semantics from semantic spaces has been +introduced by Fortuna et al.\cite{fortuna09visualization}. Their approach +focused on finding key words that existed in multiple spaces, and defining a +concrete set of semantics for these landmark words. As semantics from distinct +spaces are created, they can be evaluated according to their relation to these +landmark terms, and at any point in time, the words most closely associated to +the landmark provide terms describing events related to the landmarks. + +Sagi et al. propose an alternate approach of uses a single corpus and includes +temporal semantics after generating an initial set of +semantics\cite{SagiSemanticDensity}. This generates semantic vectors for a +corpus spanning many time ranges of interest and reducing dimensionality via +SVD. Then, to develop temporal semantics for a term, documents from a specific +time range are used to generate temporal vectors through a process very similar +to Random Indexing; in this process the first set of semantic vectors generated +are used in place of index vectors when using equation +\eqref{eq:random_indexing}. + +While these approaches allow for accurate representations of semantic shifts, +they face significant challenges when scaling to a large streaming set of +documents, due to a reliance on the SVD for dimensionality reduction. +Additionally, none of the algorithms are able to change the time-spans used for +analysis without reprocessing some portion of a corpus. Given these +limitations, a computationally efficient modification to how a semantic space is +produced is necessary to permit more detailed analysis of changing semantics. + +\section{Temporal Random Indexing} + +Temporal Random Indexing (TRI) incorporates time by building a single semantic +space. However, instead of using a word $\times$ semantics matrix, TRI uses a +word $\times$ semantics $\times$ time tensor. Figure \ref{fig:tensor-space} +illustrates this change. The time dimension records the semantic vectors of a +word for each time unit (e.g. a week or month). + +TRI offers three major advantages over existing models. First, the semantic +space is built incrementally so new documents may be added at any time. Second, +the tensor representation allows for arbitrary time-range comparisons. Third, +we use a dimensionality reduction similar to that of Random Indexing, which +operates as the documents are processed, rather than all at once. This results +in greatly reduced time and memory requirements compared to those methods that +rely on the SVD for dimensionality reduction. + +To associate specific time values with semantics, TRI does not +immediately perform the summation as defined in equation +\eqref{eq:random_indexing}. Instead TRI only accumulates the semantics for +contexts which occur in the same time period. These time period semantics are +then stored in chronologically ascending order to produce a semantic slice for a +word. The plane in figure \ref{fig:tensor-space} represents the semantic slice +of a single word, which covers all the time periods in which that word has been +observed. + +Summing a semantic slice along the time dimension produces a vector equivalent +to the results of Random Indexing, which would simply sum all the values, +ignoring time, to create a single vector for the word. TRI, on the other hand, +allows for more precise summations to be computed, such as a summation over the +entire known time range, a single point in time, or several separate time +ranges. Considering the example of a new toy that is first introduced and +later found to be toxic, figure \ref{fig:temporal-semantics} shows how one could +produce two semantic vectors for the toy ``blick`` using a semantic slice. The +first semantic vector is a summation of temporal semantic vectors that describe +the introduction of the new toy, and the second semantic vector is a summation +of temporal semantic vectors that describe the toxic nature of the toy. Using +this technique, TRI can produce two distinct semantic representations of the +same word, based on a simple partition of the temporal dimension. More over, +these two vectors can be still be directly compared because they are built from +the same index vectors. + +\begin{figure} \center +\includegraphics[width=.49\textwidth]{figures/time-tensor.eps} +\caption{The tensor representation of the semantic space} +\label{fig:tensor-space} +\end{figure} + +\begin{figure} \center +\includegraphics[]{figures/blick-semantic-slice.eps} +\caption{The semantic slice of ``blick`` as the meaning changes due to shifts in + word co-occurrence patterns} +\label{fig:temporal-semantics} +\end{figure} + +Temporal Random Indexing can be formally described as a modification of equation +\eqref{eq:random_indexing}, with three additional equations. As input, it takes +an annotated collection of documents $D = ( (t_0, d_0), (t_1, d_1), (t_2, d_2), +..., (t_k, d_k))$, where $d_i$ is the set of documents occurring at time $t_i$. Let +$W_D$ be the set of all unique words in the collection. Just as in Random +Indexing, for each word $w \in W_D$, we assign a unique index $index(w)$. + +Equation\eqref{eq:random_indexing} can then be extended to be: +\begin{equation}\label{eq:tri_temporal_semantic} + semantics(w, t) = \sum_{c_t \in d_i} \sum_{ -n \leq i \leq n} index(w_i) +\end{equation} + +where $t$ is a unique timestamp, and $c_t$ is the context for an occurrence of +$w$ at time $t$. Using this new definition of semantics, a word slice can be +defined as: +\begin{equation}\label{eq:tri_temporal_slice} + slice(w) = \{ (t_i, semantics(w, t_i) | w \in d_i, i=1,k \} +\end{equation} + +The semantics of a word for some range of time can then easily be computed with: +\begin{equation}\label{eq:tri_temporal_snapshot} +snapshot(w, t_i, t_j) = \sum_{(t_m, s_m) \in slice(w), t_i \leq t_m \leq t_j} s_m +\end{equation} + + +\section{Experiments} + +We applied TRI to the task of detecting events for a manually selected set of +199 words from a variety of topics. We selected words based on how frequently +it was used in a corpus and knowledge that it would be likely to be discussed in +blogs. However, limiting the word selection was done for efficiency, and this +approach could be applied to tracking events for a larger set of words. Due to +limited space, we illustrate the performance using a set of six word of +divergent topics that includes both abstract and specific concepts: college, +Lebanon, nuclear, Wii, PS3, and XP. + +\subsection{The Corpus} +\label{sec:corpus} + +Our approach can be applied to any corpus that has a known date of authorship +of each article, at the granularity desired for analysis of semantic shifts. +For the purpose of detecting changes in public opinion over the course of recent +events, and the detection of previously unknown, but still interesting, events, +we have utilized a portion of an already existing corpus\cite{sia08efficient}. + +The corpus comes from a collection of blog postings from 2004 on. These blog +postings come from around the world, and in a variety of languages. We view +this as an excellent example of an unstructured corpus for event detection since +it is composed of blog articles harvested by +BlogLines\footnote{http://www.bloglines.com}. The documents come from some +standard news sources, but also from any blogging service which provides rss +feeds, such as livejournal, local newspapers, wordpress, and many more. + +For this experiment, we collected only English articles from the blog corpus, +but the algorithm could be used in practice with any language. The date of +authorship for each document in this collection is estimated to be the most +recent date the document has been updated. + +Overall we expect this corpus to be well fitted to the challenge of detecting +events while handling multiple view points beyond editorial control. Table +\ref{tab:sample_blogs} provides three sample blog posts which exemplify the +issue. Each of the posts were written near the release of the Wii game console, +each with a significantly different usage of words, and sentiment. There is a +clear range of styles, from the mechanical description of the device, to +opinions on the company releasing the system, and finally to adoration of the +system. Beyond this sample set of posts, the corpus meets our expectations in +other ways. First, the lack of editorial oversight in the documents leads to +grammatical and spelling errors, and frequently to the introduction of new terms +or phrases unique to the author along with other issues\footnote{This may lead +to an increase in polysemy and synonomy amongst words, potentially impacting our +approach, but exploration of this topic is left for future work}. Second, the +corpus has a large number of discussed topics, ranging from international +events, to product releases, and to personal musings. + +\begin{table*}[tb] +\centering {\footnotesize +\begin{tabular*}{\textwidth}{ p{.3\textwidth} p{.25\textwidth} p{.38\textwidth} } +\hline + +For those of you who went, I hope you guys had just as much fun as I did. One +of the best parts was actually being able to play the Wii. When I picked up +that controller, I was sold instantly. The other awesome part was being able to +demo for Enchanted Arms in the Ubisoft area. I have a bunch of pictures up on +my Flickr Account if people are interested. & + +With motion-sensing controls and three-dimensional movements on screen, the +upcoming Nintendo Wii game platform is changing the way video game developers +think about games. +& + +While I agree that expanding video games beyond its core audience is certainly +an intriguing idea (if not necessary), it doesn't exactly thrill me as a member +of said audience. Nintendo has already done a fine job of turning us all into +their little marketing minions with the DS. None of this will change with the +Wii. I call it exploitation of the weak spot in our hearts for the big N. \\ + +\hline +\end{tabular*}} +\caption{Contrasting blog entries about the Wii gaming console prior to its + release in November 2006} +\label{tab:sample_blogs} +\end{table*} + +Before the corpus is used for performing event detection, the corpus is +preprocessed to render it more uniform. Similar to other semantic space +approaches that used web-gathered data\cite{rohde09improved}, this +pre-processing allows the model to gracefully handle several irregularities in +writing style, such as inconsistent use of punctuation and capitalization. +Additionally, this process removes many tokens such as html mark-up, which have +little or no semantic content in themselves\footnote{We note that the HTML might +be interpreted to yield more information however, TRI is agnostic to its input, +and so no special HTML processing is done}. The corpus is processed as follows: +{\small +\begin{enumerate} + \setlength{\itemsep}{1pt} + \setlength{\parskip}{0pt} + \setlength{\parsep}{0pt} + + \item Replace all numbers with $<$num$>$ + + \item Remove all html mark-up and email addresses + + \item Remove unusual punctuation, and separate all other punctuation from words + + \item Remove words of 20 characters in length + + \item Converting all words to lower case + + \item Replacing \$5 to $<$num$>$ dollars + + \item Discard articles with fewer than some threshold percentage of correctly + spelled English words + + % \item Discard duplicate articles according to a 128 bit hash. + + \item Associate each entry with a numeric timestamp + +\end{enumerate}} +When computing the semantics, we also impose two filters on corpus during +processing: any word in a list of frequent closed-classed words and those words +not in the most frequent 250,000 words in the blog corpus were removed. This +step is both practical and empirically motivated. + +Removing closed-class is a common practice in semantic spaces +models\cite{rohde09improved, sahlgren08permutations}, due to the low semantic +value; words such as ``the'' or ``of'' so frequently appear that they do not +serve to distinguish the meaning of any co-occurring word. Similarly, +infrequent words can safely be removed for initial uses due to the small effect +they would have on other semantic vectors. + +For both stop words and infrequent words, their original position is preserved +after removal. This ensures that the window for counting co-occurrence takes +into account the words originally within the window distance. All remaining +words and tokens are assigned an index vector for computing the semantics. + +We limited the analysis to the 2006 postings in the corpus; this constituted +15,725,511 blog entries and a total of 2.62 billion tokens (both words and +punctuation) after the normalization process. + +\subsection{Detecting Events using TRI} + +Events are extracted using a three step process. First, TRI is used to convert +the corpus into semantic slices. A month-long time span was selected after an +empirical analysis of the particular corpus showed that the the reduced +frequency of words in smaller time spans led to semantics that performed less +well. TRI was configured using 10,000 dimensional vectors with a $\pm 3$ word +window. Index vectors had the values of 4 dimensions randomly assigned to $+1$ +or $-1$, and the rest to be $0$. Processing the entire corpus using TRI took +approximately 100 minutes on a 2.4GHz Intel Core 2 processor with 8 gigabytes of +RAM. + +In the second step, the semantic shift is calculated for each word. To detect +the shift, a word's semantic vectors for slices at time $t_i$ and $t_{i+1}$ are +compared using the cosine similarity, which measures the similarity in angle +between vectors. The cosine similarity ranges between $1$ and $-1$, indicating +identical and opposing angles, respectively. The semantic shift is defined as +the $1 -\ $ the cosine similarity. +Changes in angle reflect a change in a word's meaning, which in this system can +signify the presence of an event. Changes in magnitude were also tracked but an +analysis showed they were not correlated with events. Table +\ref{tab:shift-table} shows semantic shifts for several test words. + +\begin{table*}[htb!f] + +\begin{tabular*}{\textwidth}{ @{\extracolsep{\fill}} | r | c c c c c c c c c c c | } + +\hline +& Feb & Mar & Apr & May & Jun & Jul & Aug & Sep & Oct & Nov & Dec \\ \hline + +college & 0.00 & 0.00 & 0.00 & 0.00 & 0.05 & 0.05 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\ \hline + +Lebanon & 0.04 & 0.05 & 0.05 & 0.06 & {\bf 0.16} & {\bf 0.25} & 0.01 & 0.01 & 0.02 & 0.03 & 0.01 \\ \hline + +nuclear & 0.02 & 0.02 & 0.02 & 0.02 & 0.02 & 0.02 & 0.02 & 0.01 & {\bf 0.11} & 0.06 & 0.02 \\ \hline + +PS3 & 0.06 & 0.04 & 0.06 & 0.05 & 0.03 & 0.04 & 0.03 & 0.02 & 0.02 & 0.03 & 0.01 \\ \hline + +Wii & {\bf 0.12} & {\bf 0.14} & {\bf 0.15} & 0.06 & 0.03 & 0.04 & 0.04 & 0.02 & 0.01 & 0.01 & 0.01 \\ \hline + +XP & 0.03 & 0.04 & 0.03 & 0.03 & {\bf 0.19} & {\bf 0.20} & 0.02 & 0.02 & 0.02 & 0.02 & 0.01 \\\hline + +\end{tabular*} +\caption{Semantic shift values for six example words where bold indicates a + significant change} +\label{tab:shift-table} +\end{table*} + +The third step selects those topic words that undergo a significant semantic +shift and associate the topic words with documents. We define the significance +for a shift in terms of its deviation from the mean semantic shift using a +simple time series analysis. Specifically, we calculate the mean and standard +deviation for the semantic shift of all words in the two slices. If a word's +shift is greater than one standard deviation away from the mean, then it the +word is marked as undergoing a significant shift. The bold values in table +\ref{tab:shift-table} note these shifts for five example words. + +To form the association between documents and topic words, each word that +undergoes a significant shift has its nearest neighbors calculated. These +neighbors are often words associated with the topic word, but are not +necessarily synonyms. We posit that the neighbors provide context about the +nature of an event by virtue of reflecting the frequent co-occurrences in the +documents. To retrieve the event-related documents, the topic word and its +neighbors are used as query terms to search the corpus during the month that the +event occurred. Documents are retrieved using a simple technique that returns +the posts containing the event term and the highest frequency of the related +terms. + +Accurately evaluating event detection requires a set of events that are known a +priori to bein the corpus. For large corpora with millions of documents, such +as the Bloglines corpus used here, it is infeasible to determine the complete +set of events that are present. Furthermore, determining what kinds of events +may be present can prove problematic, as blogs frequently discuss many topics +outside the range of normal news events. To create a baseline for evaluation, +We constructed a limited set of significant news events that were likely to be +in the corpus and then manually verified their presence. Descriptive keywords +for each event were then to evaluate TRI. Ultimately, the evaluation is an +analysis of not only TRI, but also the corpus itself, as some terms, or events, +may not be present at all within the corpus. We plan to use this initial +methodology to identify a better means of analyzing massive corpora and +the diverse set of events contained therein. + + +\subsection{Results} + +Several semantic shifts correlated well with known events of 2006. We discuss +the results by analyzing the events detected for the words in table +\ref{tab:shift-table}. Table \ref{tab:event-blogs} lists some of the highest +rated blogs associated with specific events our technique detected. + +Both the ``Wii'' and the ``PS3'' are gaming consoles released in North America +in November 2006. However, only the Wii experienced a significant semantic shift. +The stabilization of the semantics correlates with the products demonstration at +the Electronics Entertainment Expo, a major gaming event. The corpus contained +many examples of attendees describing their experiences with both consoles at +the convention. Notably the PS3 underwent only a slight shift, indicating +a fairly stable meaning. Further analysis showed that the change in ``Wii'' was +due to the console being renamed from ``Revolution'' to ``Wii'' in late April. + +The 2006 Lebanon War took place in July 2006, which was detected by a +significant shift in meaning and is further supported by a change in the +nearest neighbors. In July, the nearest neighbors of ``Lebanon'' were terms +associated with war, such as ``Hezbollah'', ``soldiers'', and +``rockets''. However, before, and after the war, the ten closest neighbors to +``Lebanon'' in 2006 were names of countries, revealing that during the course of +the war, the semantics of ``Lebanon'' shifted dramaticly to a different class of +words, and then returned to it's original class once the war concluded. + +The changes for ``nuclear'' correspond directly to claims that North Korea +conducted nuclear tests in October 2006. Until October, the related terms of +``nuclear'' are focused on Iran, and nuclear power; during +October, the neighbors shift towards terms such as ``Korea'', ``atomic'', +``sanctions'', and ``bomb.'' + +Throughout the year, ``college'' experienced no noticeable semantic shifts, +despite the annual events of beginning and graduating college. We view this as +example of a consistent word which acts as a reference point to other words. + +An analysis for ``XP'' showed a semantic shift caused by an unlikely change in +corpus content; during the month of June, spammers added such a high number of +advertisements for Windows XP copies, shifting the semantics to unimportant +terms. An examination of the nearest neighbors to ``XP'' showed a dramatic +change from related operating system terms such as ``Windows,'' ``Linux'' and +``Vista'' to numbers and currency abbreviations. + +Overall, using the cosine similarity metric, and then further examining the sets +of nearest neighbors proved to be an effective method of catching semantic +shifts. Furthermore combining the nearest neighbors with a simple document +retrieval algorithm generated relevant documents corresponding to the events +which caused the shift. + +\begin{table*}[tb] +\centering {\footnotesize +\begin{tabular*}{\textwidth}{ p{.31\textwidth} p{.31\textwidth} p{.31\textwidth} } +\hline + +\multicolumn{1}{c}{Lebanon} & \multicolumn{1}{c}{nuclear} & \multicolumn{1}{c}{Wii} \\ +\hline + +Exercising great restraint, they instantly launched airstrikes on Lebanon, +damaging critical roads, [...], power stations, etc. Hezbollah +retaliated with a stream of rockets that penetrated as far Ashaifa, causing a +great deal of terror to Israeli civilians. + +& + +Pyongyang would not hold negotiations to resolve the outstanding issues with +Washington, [...] ``the Americans never recognized our security and we were +forced to conduct nuclear test to defend ourselves.'' + +& + +The Wii was the name of the console.. It was time to see if it could deliver its +promise of ``changing the way we game.'' Their presentation was probably the +most ``fun,'' cutting right to the chase and demonstrating uses of the +controller in games. + +\\ + +[T]heir goal is to move public opinion in Lebanon against Hezbollah due to the +destruction ``they'' caused the country, establish a strong deterrence for any +future attacks, and , of course, destroy as much of Hezbollah's infrastructure +and weapons as possible. + +& + +Korea nuclear test hasn't tipped military balance [...] hours ago questions +surrounding North Korea and its nascent nuclear weapons program took center +stage Monday night + +& + +It turns out, according to eyewitness reports from the show floor, that +we might not have been playing Wii consoles at the Nintendo booth...should I +feel betrayed? \\ \hline +\end{tabular*}} +\caption{Blog snippets describing events associated with ``Lebanon'' in +July, ``nuclear'' in October, and ``Wii'' in May} +\label{tab:event-blogs} +\end{table*} + + + +\section{Related Work} +\label{sec:related-work} + +Among the many systems that perform event detection, several use a related +technique that maps documents, rather than words, into a vector space. +Documents are represented by a vector of their term frequencies, with most +approaches using some form of weighting the vectors, such as term +frequency-inverse document frequency (TF-IDF) weighting. Additionally, many +event detection systems restrict themselves to processing newswire text, instead +of blogs. + +Most document based event detection algorithms extend a core usage of TF-IDF +weighting. In the core event detection algorithm, each document is analyzed to +produce TF-IDF values for each word occurring in the document. This set of +values can then be compared against TF-IDF values of other documents using the +same similarity measures used in semantic space models, with cosine similarity +being one of the most common. In general, an event is detected if the current +document is significantly different from all other processed documents, based on +a threshold of similarity values between +documents\cite{brants03ned,kumaran04entityevent}. + +Brants et al. introduced some significant improvements to the standard document +based model\cite{brants03ned}. The first improvement was to compute the TF-IDF +values on a document by document basis, allowing the system to continuously +process new documents. The second improvement was computing a set of TF-IDF +values which were dependent on the source of the document, under the assumption +that some words, such as CNN, would be more frequent based on who wrote the +document. Beyond modifying the TF-IDF values, the similarity measure was also +extended to include some normalization techniques that take into consideration +the source of the documents, and the average similarity of documents. Finally, +their model was extended to compare segmentations of documents, rather than +entire documents. Overall, these modifications showed noticeable improvements +over the basic usage of TF-IDF values and similarity metrics. + +Kumaran and Allan expand on Brants et al. by considering not only the term +frequencies when computing the similarity between documents, but also named +entities, such as ``President Obama,'' in the +documents\cite{kumaran04entityevent}. Two additional vectors are created for +each document: One composed of just the named entities occurring in a document, +and another composed of all words that are not named entities. When comparing +the similarity between two documents, the standard vector is initially used, and +then the similarity between the additional vectors are used to provide finer +distinctions, such as whether two documents refer to the same set of named +entities, and the same set of general topics, i.e. all the non named entities. + +In \cite{lam01contextual}, Lam et al. extend a document-space approach by +associating each document with three vectors: a TF-IDF weighted vector; a TF-IDF +score of named entities present in the document, similar to +\cite{kumaran04entityevent}; and a concept vector, which details which abstract +concepts are contained in the document, using TF-IDF scores based on the +frequency of concepts rather than words. The key terms in a document are each +given a weight based on which key terms the document contains. Event detection +is done by clustering documents as they appear. Each cluster is said to +represent a specific event; and documents that do not fit into one cluster are +said to be new events. Chen et al. use a similar clustering for event detection +but use sentences rather than entire document\cite{chen07hot}. + +Makkonen et al. augment the document representation by using an existing +ontology to extract out locations, proper names, and temporal references +from the document\cite{makkonen04simple}. These three, combined +with the remaining terms in the document are used as the basis for comparison. + +Overall, the current event detection systems that do not utilize a semantic +space have the key benefit of being able to process documents continuously, +since no reduction step is required for vector representations. But the key +difference is the focus on comparisons between documents, and not words that +occur in documents. These approaches must handle different challenges, such as +documents that discuss multiple events and elements of documents that are +vague but important for distinguishing events. + +\section{Discussion} + +The semantic space model we have presented has a number of benefits and +drawbacks compared to other semantic space and document based techniques for +automatic event detection. The most significant outstanding question is how to +analyze all the semantic slices produced in an efficient manner that exposes +events. While our preliminary analysis has shown that events can be detected +using TRI, our approach does not currently scale to searching across all terms, +nor to identifying events for new words that infrequently occur. However, we +argue that the advantages provided by TRI outweigh the outstanding issues and +merits further work to address these limitations. + +Event detection systems that use semantic spaces have two notable challenges due +to how time is integrated. First, the space must be easily modifiable as new +documents are produced. Existing approaches use a single dimensionality +reduction step after a corpus had been processed to improve information +retrieval. However this step limits the integration of new documents into the +semantic space; to integrate new documents, the space must be completely +recomputed. The second challenge stems from comparing word meanings and +documents that occur in different times. Approaches such as +\cite{kontostathis04use,fortuna09visualization} that arbitrarily segment the +corpora used into different semantic spaces artificially limit both the types of +comparisons available and the specific time ranges of the semantics. TRI +addresses both of these challenges efficiently. By being based on Random +Indexing, dimensionality reduction is done concurrently with developing semantic +vectors. Additionally, by utilizing the same set of index vectors over all +documents analyzed, every semantic slice is contained within the same semantic +space, avoiding the need for reference only those vectors that are common to +several time periods. + +Conversely, the document based methods discussed in section +\ref{sec:related-work} provided a means of avoiding a post processing stage by +incrementally determining the TF-IDF values for words in the corpus. While +these approaches efficiently allow the inclusion of more documents over time, +each document vector encounters similar problems seen in basic co-occurrence +semantic space models, most notably the requirement that two documents have the +same exact words for them to be declared similar. + +The introduction of additional vector representations of a document, such as the +named entity vectors, or the concept vectors, attempt to address this issue, but +these additions allude to benefits provided by a semantic space model. For +instance, if two documents describe the same events, but without using the same +set of words, and instead use highly similar words to describe the event +differently, the document based event detection methods would either report two +distinct events, or rely on some system which can determine the similarity +between two words. Being based on word semantics, TRI avoids this problem, and +provides a way of determining how similar two terms are, or which concepts a +word refers to. With TRI, synonymous key words describing the event are +modified in a similar manner, and words with similar meanings will have similar +effects on the semantics. It may also be possible with TRI to detect synonymous +event names by identifying words with similar shifts and similar neighbors. +However, further investigation is needed. + +While TRI provides elegant solutions to several problems in event detection, +significant questions still remain. First, a suitable method of analyzing the +semantic shift between vectors is needed. Our initial experiment illustrates +tracking outliers based on cosine similarity works well in practice; however, +this does not utilize all the information present and could leave some events +undetected. Time series analysis or probability distribution analysis are two +techniques which might be well suited for similarity comparisons between +semantic slices. +However, it remains an open question of what limitations exist to the types of +events TRI can be detected, and whether the method of comparison can be targeted +to find specific kinds of events. + +As a second issue, the relationship should be established between the corpus, +the duration of a semantic slice, and the types of events that are detected. +Our current system was able to detect changes at a monthly granularity, but +real-time event detection must operate on a much finer scale. Further work is +needed to determine how brief a semantic slice can be while still adequately +representing the semantics necessary for event detection. + +Regarding the granularity of semantic slices and semantic vectors, we suspect +that the optimal granularity is highly dependent on how dense documents are with +regards to time in the corpus. One drawback of Random Indexing is the need for +a large amount of data, and if there is not enough data, semantic vectors become +poorly defined and produce weak similarity scores. We found that the corpus +used in the experiment was sparse enough to produce a degradation in the +semantics when our semantic slices were set to a time range shorter than a +month. Ideally the corpus should have a dense enough set of topics for very +narrow semantic slices. + +\section{Conclusion} + +Unstructured, unfiltered corpora such as blogs present an ideal opportunity for +automated event-detection systems to identify new events before they can be +reported through more formal sources. We have presented an algorithm that uses +changes in word semantics to detect new events in blog posts. Our approach +utilizes simple word co-occurrence and scales well to processing millions of +blog posts. Additionally, initial experiments to identify events for specific +words proved successful. Further work is needed to identify the strengths and +weakness of this approach and quantify its ability to detect events. However, +we plan to address these issues in future work. Last we plan to release the +implementation of TRI as a part of the S-Space Package\cite{jurgens09sspace}. + +\section*{Acknowledgements} + +We thank John Cho and his lab for access to the blogline corpus used in this +work. We also thank the anonymous reviewers for their comments and suggestions. + +\bibliographystyle{abbrv} \bibliography{cml_paper} + +\end{document} diff --git a/papers/2009_ranlp_ettt_temporal_random_indexing/figures/blick-semantic-slice.eps b/papers/2009_ranlp_ettt_temporal_random_indexing/figures/blick-semantic-slice.eps new file mode 100644 index 00000000..0e9e764f --- /dev/null +++ b/papers/2009_ranlp_ettt_temporal_random_indexing/figures/blick-semantic-slice.eps @@ -0,0 +1,384 @@ +%!PS-Adobe-3.0 EPSF-3.0 +%%BoundingBox: 1 758 133 835 +%%Title: blick-semantic-slice +%%CreationDate: Tue Jun 2 13:32:13 2009 +%%Creator: Tgif-4.1.45-QPL written by William Chia-Wei Cheng (bill.cheng@acm.org) +%%ProducedBy: (unknown) +%%Pages: 1 +%%DocumentFonts: (atend) +%%EndComments +%%BeginProlog + +/tgifdict 89 dict def +tgifdict begin + +/tgifarrowtipdict 8 dict def +tgifarrowtipdict /mtrx matrix put + +/TGAT % tgifarrowtip + { tgifarrowtipdict begin + /dy exch def + /dx exch def + /h exch def + /w 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b/papers/2009_ranlp_ettt_temporal_random_indexing/ranlp.cls new file mode 100755 index 00000000..b03e8856 --- /dev/null +++ b/papers/2009_ranlp_ettt_temporal_random_indexing/ranlp.cls @@ -0,0 +1,73 @@ +%------------------------------------------------------------------------ +% FILE : ranlp.cls +% DATE : 2007-03-03 +% LaTeX version : LaTeX2e +% AUTHOR : Nicolas Nicolov ({first}_{surname} at yahoo com) +%------------------------------------------------------------------------ + +\LoadClassWithOptions{article} + +\usepackage{epsfig} +%\usepackage[dvips]{graphicx} + +\usepackage{amssymb} +\usepackage{amsmath} +\usepackage{amsfonts} + +\usepackage{ranlpmacros} + + +%------------------------------------------------------------------------ +% Physical page layout +%------------------------------------------------------------------------ + +% A4 sheet = 210mm x 297mm / 8.25in x 11.625in + +\setlength\topmargin{-5.2mm} +\setlength\oddsidemargin{-5.4mm} +\setlength\evensidemargin{-5.4mm} +\setlength\textheight{247mm} +\setlength\textwidth{170mm} +\setlength\columnsep{0.2in} +\newlength\titlebox \setlength\titlebox{1.75in} +\setlength\headheight{0pt} \setlength\headsep{0pt} +% \setlength\footheight{0pt} +\setlength\footskip{30pt} +\flushbottom \twocolumn \sloppy + +%------------------------------------------------------------------------ + +\renewenvironment{abstract} + {\centerline{\large\bf Abstract}\vspace*{-1ex} + \begin{small}\begin{quote}} + {\par\end{quote}\end{small}\vskip 1ex} + +%------------------------------------------------------------------------ +% Captions are in italic +%------------------------------------------------------------------------ + +\long\def\@makecaption#1#2{ + \vskip 10pt + \setbox\@tempboxa\hbox{\textbf{#1:} \textit{#2}} + \ifdim \wd\@tempboxa >\hsize % IF longer than one line: + \textbf{#1:} \textit{#2}\par % THEN set as ordinary paragraph. + \else % ELSE center. + \hbox to\hsize{\hfil\box\@tempboxa\hfil} + \fi} + +%------------------------------------------------------------------------ + +%%% Reduce distance between baselines: + +\renewcommand{\baselinestretch}{0.9} + + +%--- NN: CHANGING HOW THE FOOTNOTE LOOKS: ------------------------------- +% Put indentation between the footnote marker and the text of the footnote. + +\makeatletter +\long\def\@makefntext#1{\@setpar{\@@par\@tempdima \hsize + \advance\@tempdima-10pt\parshape \@ne 10pt \@tempdima}\par + \parindent 1em\noindent \hbox to \z@{\hss$^{\@thefnmark}\ $}#1} +\makeatother +%------------------------------------------------------------------------ diff --git a/papers/2009_ranlp_ettt_temporal_random_indexing/ranlpmacros.sty b/papers/2009_ranlp_ettt_temporal_random_indexing/ranlpmacros.sty new file mode 100755 index 00000000..58d6a3fa --- /dev/null +++ b/papers/2009_ranlp_ettt_temporal_random_indexing/ranlpmacros.sty @@ -0,0 +1,166 @@ +%--------------------------------------------------------------------- +% +% FILE : ranlpmacros.sty +% DATE : 2007-03-03 +% AUTHOR: Nicolas Nicolov +% +%--------------------------------------------------------------------- + +\newcommand{\ranlp}{\textsc{ranlp}} +\newcommand{\email}[2]{\emph{#1}@\emph{#2}} +\newcommand{\keywords}[1]{\subsection*{Keywords} {\footnotesize #1}} +\newcommand{\url}[1]{\texttt{#1}} + +\renewcommand{\figurename}{Fig.} % use "Fig." for the figure name! + +% How much space to leave before the caption +\setlength\abovecaptionskip{1.3ex minus 0.8ex} % originally 10\p@ in ranlp_bk.cls +% How much space to leave after the caption +\setlength\belowcaptionskip{1em minus 1ex} % originally 0\p@ in ranlp_bk.cls + +%--------------------------------------------------------------------- +% FIGURES +%--------------------------------------------------------------------- +% \ranlpfig{WIDTH}{FILE}{LABEL}{CAPTION} +\newcommand{\ranlpfig}[4]{ + \begin{figure}[thb] + \vspace*{-1ex} + \hrule\vspace*{2ex minus 1ex} + \begin{center} + \mbox{ + \epsfxsize=#1\textwidth + \epsfbox{#2}} + \end{center} + \vspace*{-1.5ex} + \caption{#4}\label{#3} + \hrule\vspace*{-2ex}\vspace*{0.5ex minus 0.4ex} + \end{figure}} + +%--------------------------------------------------------------------- + + +%--------------------------------------------------------------------- +% COMPUTATIONAL LINGUISTIC TERMS +%--------------------------------------------------------------------- + +\newcommand{\cl}{{\sc cl}} % Computational Linguistics +\newcommand{\nl}{{\sc nl}} % Natural Language +\newcommand{\nlp}{{\sc nlp}} % Natural Language Processing +\newcommand{\nlu}{{\sc nlu}} % Natural Language Understanding +\newcommand{\nla}{{\sc nla}} % Natural Language Analysis +\newcommand{\nlg}{{\sc nlg}} % Natural Language Generation +\newcommand{\tg}{{\sc tg}} % Text Generation +\newcommand{\mt}{{\sc mt}} % Machine Translation +\newcommand{\ir}{{\sc ir}} % Information Retrieval +\newcommand{\ie}{{\sc ie}} % Information Extraction +\newcommand{\wsd}{\textsc{wsd}} % Word Sense Disambiguation +\newcommand{\qa}{{\sc qa}} % Question Answering +\newcommand{\lsa}{{\sc lsa}} % Latent Semantic Analysis +\newcommand{\lsi}{{\sc lsi}} % Latent Semantic Indexing +\newcommand{\SVD}{{\sc svd}} % Singular Value Decomposition +\newcommand{\tfidf}{\mbox{tf$\cdot$idf}} % TFIDF +\newcommand{\fs}{{\sc fs}} % Finite State +\newcommand{\fsa}{{\sc fsa}} % Finite State Automata +\newcommand{\clp}{{\sc clp}} % Constraint Logic Programming +\newcommand{\is}{{\sc is}} % Information Structure +\newcommand{\topic}{{\sc Topic}} % Topic +\newcommand{\focus}{{\sc Focus}} % Focus +\newcommand{\NE}{{\sc ne}} % Named Entity +\newcommand{\atn}{{\sc atn}} % Augmented Transition Networks +\newcommand{\DAG}{{\sc dag}} % Directed Acyclic Graph +\newcommand{\chart}{$\cal C$} % Chart + +\newcommand{\UIMA}{{\sc uima}} % Unstructured Information Management Architecture +\newcommand{\GATE}{{\sc gate}} % GATE +\newcommand{\tipster}{{\sc tipster}} % Tipster +\newcommand{\JET}{{\sc jet}} % Jet +\newcommand{\trec}{{\sc trec}} % TREC + + +% PROGRAMMING LANGUAGES + +\newcommand{\java}{{\sc Java}} % Java +\newcommand{\python}{{\sc Python}} % Python +\newcommand{\ruby}{{\sc Ruby}} % Ruby +\newcommand{\prolog}{{\sc Prolog}} % PROLOG +\newcommand{\lisp}{{\sc Lisp}} % LISP +\newcommand{\life}{{\sc Life}} % LIFE +\newcommand{\oz}{{\sc Oz}} % Oz +\newcommand{\perl}{{\sc Perl}} % Perl + + +% MACHINE LEARNING FRAMEWORKS + +\newcommand{\DT}{{\sc dt}} % Decision Trees +\newcommand{\HMM}{{\sc hmm}} % Hidden Markov Models +\newcommand{\KNN}{{\sc knn}} % k-Nearest Neighbour +\newcommand{\SVM}{{\sc svm}} % Support Vector Machines +\newcommand{\TBL}{{\sc tbl}} % Transformation-Based Learning +\newcommand{\ME}{{\sc me}} % Maximum Entropy +\newcommand{\SNoW}{{\sc SNoW}} % SNoW +\newcommand{\RMM}{{\sc rmm}} % Robust Risk Minimization + + +% LINGUISTIC FRAMEWORKS + +\newcommand{\cfg}{{\sc cfg}} % Context Free Grammar +\newcommand{\cfgs}{{\sc cfg}s} % Context Free GrammarS +\newcommand{\cf}{{\sc cf}} % Context Free +\newcommand{\pcfg}{{\sc pcfg}} % Probabilistic Context Free Grammar + +\newcommand{\pos}{{\sc pos}} % part-of-speech + + +\newcommand{\ptb}{{\sc ptb}} % Penn Tree Bank +\newcommand{\bnc}{{\sc bnc}} % British National Corpus + + +\newcommand{\gpsg}{{\sc gpsg}} % Generalised Phrase Structure + % Grammars +\newcommand{\hpsg}{{\sc hpsg}} % Head Driven Phrase Structure Grammar +\newcommand{\mtt}{{\sc mtt}} % Meaning Text Theory +%\newcommand{\tag}{{\sc tag}} % Tree-Adjoining Grammar -- defined by a package that is loaded +\newcommand{\ltag}{{\sc ltag}} % Lexicalised Tree-Adjoining Grammar +\newcommand{\dtg}{{\sc dtg}} % D-Tree Grammar +\newcommand{\dsg}{{\sc dsg}} % D-Tree SUbstitution Grammar +\newcommand{\dsgs}{{\sc dsg}s} % D-Tree SUbstitution GrammarS +\newcommand{\rst}{{\sc rst}} % Rhetorical Structure Theory +\newcommand{\sesyn}{{\sc SeSyn}}% Semantic Syntax +\newcommand{\id}{{\sc id}} % Immediate Dominance (rule) +\newcommand{\lp}{{\sc lp}} % Linear Precedence (statements) + +% SOME SYSTEMS + +\newcommand{\WordNet}{{\sc WordNet}} % WordNet +\newcommand{\TNT}{{\sc tnt}} % TNT +\newcommand{\INTEX}{{\sc Intex}} % Intex +\newcommand{\jet}{{\sc jet}} % Jet +\newcommand{\patrii}{{\sc patr-ii}} % PATR-II +\newcommand{\patr}{{\sc patr}} % PATR +\newcommand{\fug}{{\sc fug}} % FUG Functional Unification Grammar +\newcommand{\fuf}{{\sc fuf}} % FUF Functional Unification +\newcommand{\tfs}{{\sc tfs}} % TFS Type Feature Structure System +\newcommand{\cuf}{{\sc cuf}} % CUF +\newcommand{\ale}{{\sc ale}} % ALE Atribute Logic Engine +\newcommand{\idas}{{\sc idas}} % IDAS Intelligent Document Advisory System +\newcommand{\mumble}{{\sc mumble}} % McDonald's MUMBLE +\newcommand{\spokesman}{{\sc spokesman}} % Marie Meteer +\newcommand{\wip}{{\sc wip}} % Wolfgang Wahlster +\newcommand{\nigel}{{\sc nigel}} % NIGEL generator (ISI) +\newcommand{\komet}{{\sc komet}} % KOMET system (John Bateman) +\newcommand{\protector}{{\sc protector}} % Nicolov-Mellish-Ritchie +\newcommand{\xtag}{{\sc xtag}} % XTAG system +\newcommand{\spud}{{\sc spud}} % Matthew Stone & Christine Doran +\newcommand{\hush}[1]{} % don't show it ! + +\newcommand{\cat}[1]{{\small\uppercase{#1}}} % for syntactic categories +\newcommand{\nct}[1]{{\sf #1}} % for syntactic categories in trees +\newcommand{\anch}[1]{\mbox{\ct{#1}$\diamond$}} + +% Some commands to handle linespacing + +\newlength{\spacing} +\setlength{\spacing}{\baselineskip} + +\newcommand{\nspace}[1]{\setlength{\baselineskip}{#1\spacing}} +\newenvironment{linespacing}[1]{\nspace{#1}}{} diff --git a/papers/2010_acl_systems_sspace/acl-sspace-paper.bib b/papers/2010_acl_systems_sspace/acl-sspace-paper.bib new file mode 100644 index 00000000..0dd8e897 --- /dev/null +++ b/papers/2010_acl_systems_sspace/acl-sspace-paper.bib @@ -0,0 +1,465 @@ +@article{andrews09integrating, + author = {Mark Andrews, Gabriella Vigliocco}, + title = {Integrating Experiential and Distributional Data to Learn Semantic + Representations}, + journal = {Psychological 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Levy}, + title = {Extracting {S}emantic {R}epresentations from {L}arge {T}ext {C}orpora}, + booktitle = {Proceedings of the Fourth Neural Computation and Psychology Workshop}, + pages = {199-212}, + address = {London}, + publisher = {Springer-Verlag}, + year = 1997, +} + +@inproceedings{purandare04discriminating, + author = {Amruta Purandare and Ted Petersen}, + title = {Discriminating Among Word Meanings by Identifying Similar Contexts}, + booktitle = {Proceedings of the Nineteenth National Conference on Artificial Intelligence (AAAI-04)}, + year = 2004, + pages = {964--965}, +} + +@inproceedings{purandare04word, + author = {Amruta Purandare and Ted Pedersen}, + booktitle = {HLT-NAACL 2004 Workshop: Eighth Conference on Computational Natural Language Learning (CoNLL-2004)}, + pages = {41--48}, + publisher = {Association for Computational Linguistics}, + title = {Word Sense Discrimination by Clustering Contexts in Vector and Similarity Spaces}, + year = {2004} +} + +@inproceedings{rapp03word, + author = {Reinhard Rapp}, + year = 2003, + title = {Word sense discovery based on sense descriptor dissimilarity}, + booktitle = {Ninth Machine Translation Summit}, + address = {New Orleans}, + pages = {315--322}, +} + +@article{rehder98using, + author = {B. Rehder and M. E. Schreiner and M. B. Wolfe and D. Laham and T. K. Landauer and W. Kintsch}, + year = 1998, + title = {Using {L}atent {S}emantic {A}nalysis to assess knowledge: Some technical considerations}, + journal = {Discourse Processes}, + volume = 25, + pages = {337--354}, +} + +@article{rohde09improved, + author = {Douglas L. T. Rohde and Laura M. Gonnerman and David C. Plaut}, + title = {An Improved Model of Semantic Similarity Based on Lexical Co-Occurrence}, + year = 2009, + journal = {Cognitive Science}, + url = {http://www.cnbc.cmu.edu/~plaut/papers/abstracts/ RohdeGonnermanPlautSUB-CogSci.COALS.html}, + note = {sumitted}, +} + +@article{rubenstein65contextual, + author = {H. Rubenstein and J. B. Goodenough}, + title = {Contextual Correlates of Synonymy}, + journal = {Communications of the ACM}, + year = 1965, + volume = 8, + pages = {627--633}, +} + +@inproceedings{sahlgren05introduction, + author = {Magnus Sahlgren}, + title = {An introduction to random indexing}, + year = 2005, + booktitle = {Proceedings of the Methods and Applicatons of Semantic Indexing Workshop at the 7th International Conference on Terminology and Knowledge Engineering}, +} + +@inproceedings{sahlgren06towards, + author = {Magnus Sahlgren}, + year = 2006, + title = {Towards pertinent evaluation methodologies for word-space models}, + booktitle = {Proceedings of the fifth international conference on Language Resources and Evaluation, LREC 2006}, + location = {Genoa, Italy}, +} + +@phdthesis{sahlgren06word, + author = {Magnus Sahlgren}, + year = 2006, + title = {The Word-Space Model: Using distributional analysis to represent syntagmatic and paradigmatic relations between words in high-dimensional vector spaces}, + school = {Stockholm University, Department of Linguistics}, + address = {Stockholm, Sweden}, +} + +@inproceedings{sahlgren08permutations, + author = {M. Sahlgren and A. Holst and P. Kanerva}, + year = 2008, + title = {Permutations as a Means to Encode Order in Word Space}, + booktitle = {Proceedings of the 30th Annual Meeting of the Cognitive Science Society (CogSci'08)}, + location = {Washington D.C., USA}, +} + +@article{salton75vector, + author = {G. Salton and A. Wong and C. S. Yang}, + year = 1975, + title = "A Vector Space Model for Automatic Indexing", + journal = {Communications of the ACM}, + volume = 18, + number = 11, + pages = {613--620}, +} + +@article{salton88term, + author = {G. Salton and C. Buckley}, + year = 1988, + title = {Term-weighting approaches in automatic text retrieval}, + journal = {Information Processing \& Management}, + volume = 24, + numberm = 5, + pages = {513-–523}, +} + +@article{schutze98automatic, + author = {Hinrich Sch\"{u}tze}, + title = {Automatic Word Sense Discrimination}, + journal = {Computational Linguistics}, + year = {1998}, + volume = 24, + number = 1, + pages = {97--123}, +} + +@article{tibshirani00estimating, + author = {Robert Tibshirani and Guenther Walther and Trevor Hastie}, + title = {Estimating the number of clusters in a dataset via the Gap statistic}, + journal = {Journal Royal Statistics Society B}, + year = {2000}, + volume = {63}, + pages = {411--423} +} + +@inproceedings{turney01mining, + author = {Peter D. Turney}, + year = 2001, + title = {Mining the {W}eb for synonyms: {P}{M}{I}-{I}{R} versus {L}{S}{A} on {T}{O}{E}{F}{L}}, + booktitle = {Proceedings of the Twelfth European Conference on Machine Learning (ECML-2001)}, + location = {Freiburg, Germany}, + pages = {491--502}, +} + +@article{turney10frequency, + title={{From Frequency to Meaning: Vector Space Models of Semantics}}, + author={Peter D. Turney and Patrick Pantel}, + journal={Journal of Artificial Intelligence Research}, + volume={37}, + pages={141--188}, + year={2010} +} + +@inproceedings{weeds04characterising, + author = {Julie Weeds and David Weir and Diana McCarty}, + year = 2004, + title = {Characterising measures of lexical distributional similarity}, + booktitle = {Proceedings of the 20th International Conference on Computational Linguistics COLING'04}, + pages = {1015--1021}, +} + +@inproceedings{widdows08semantic, + author = {Dominic Widdows and Kathleen Ferraro}, + title = {Semantic Vectors: a Scalable Open Source Package and Online Technology Management Application}, + booktitle = {Proceedings of the Sixth International Language Resources and Evaluation (LREC'08)}, + year = {2008}, +} diff --git a/papers/2010_acl_systems_sspace/acl-sspace-paper.tex b/papers/2010_acl_systems_sspace/acl-sspace-paper.tex new file mode 100644 index 00000000..291288e7 --- /dev/null +++ b/papers/2010_acl_systems_sspace/acl-sspace-paper.tex @@ -0,0 +1,439 @@ +% +\usepackage{acl2010} +\usepackage{times} +\usepackage{url} +\usepackage{latexsym} +\usepackage{epsfig} +\usepackage{latexsym} +\usepackage[usenames]{color} +\usepackage{times} +\usepackage{verbatim} +\usepackage{multirow} +\usepackage{threeparttable} +\usepackage{booktabs} + +\title{The S-Space Package: An Open Source Package for Word Space Models} + +\author{ David Jurgens\\ + University of California, Los Angeles, \\ + 4732 Boelter Hall \\ + Los Angeles, CA 90095 \\ + {\tt jurgens@cs.ucla.edu} \And + Keith Stevens\\ + University of California, Los Angeles, \\ + 4732 Boelter Hall \\ + Los Angeles, CA 90095 \\ + {\tt kstevens@cs.ucla.edu}} + + +\date{} + +\begin{document} +\maketitle +\begin{abstract} + +We present the S-Space Package, an open source framework for developing and +evaluating word space algorithms. The package implements well-known word space +algorithms, such as LSA, and provides a comprehensive set of matrix utilities +and data structures for extending new or existing models. The package also +includes word space benchmarks for evaluation. Both algorithms and +libraries are designed for high concurrency and scalability. We demonstrate the +efficiency of the reference implementations and also provide their results on +six benchmarks. + +\end{abstract} + +\section{Introduction} + +Word similarity is an essential part of understanding natural language. +Similarity enables meaningful comparisons, entailments, and is a bridge to +building and extending rich ontologies for evaluating word semantics. Word +space algorithms have been proposed as an automated approach for developing +meaningfully comparable semantic representations based on word distributions in +text. + +Many of the well known algorithms, such as Latent Semantic Analysis +\cite{landauer97solution} and Hyperspace Analogue to Language +\cite{burgess97modeling}, have been shown to approximate human judgements of +word similarity in addition to providing computational models for other +psychological and linguistic phenomena. More recent approaches have extended +this approach to model phenomena such as child language acquisition +\cite{baroni07isa} or semantic priming \cite{jones06high}. In addition, these +models have provided insight in fields outside of linguistics, such as +information retrieval, natural language processing and cognitive psychology. +For a recent survey of word space approaches and applications, see +\cite{turney10frequency}. + +The parallel development of word space models in different fields has often +resulted in duplicated work. The pace of development presents a need for a +reliable method for accurate comparisons between new and existing approaches. +Furthermore, given the frequent similarity of approaches, we argue that the +research community would greatly benefit from a common library and evaluation +utilities for word spaces. Therefore, we introduce the \textbf{S-Space + Package}, an open source framework with four main contributions: +% +\begin{enumerate} + \setlength{\itemsep}{1pt} + \setlength{\parskip}{0pt} + \setlength{\parsep}{0pt} + \item reference implementations of frequently cited algorithms + \item a comprehensive, highly concurrent library of tools for building new + models + \item an evaluation framework for testing models on standard benchmarks, + e.g.\ the TOEFL Synonym Test \cite{landauer98introduction} + \item a standardized interface for interacting with all word space models, + which facilitates word space based applications. +\end{enumerate} + +The package is written in Java and defines a standardized Java interface for word +space algorithms. +% +While other word space frameworks exist, e.g.\ \cite{widdows08semantic}, the +focus of this framework is to ease the development of new algorithms and the +comparison against existing models. +% +Compared to existing frameworks, the S-Space Package supports a much wider +variety of algorithms and provides significantly more reusable developer +utilities for word spaces, such as tokenizing and filtering, sparse vectors and +matrices, specialized data structures, and seamless integration with external +programs for dimensionality reduction and clustering. +% +We hope that the release of this framework will greatly facilitate other +researchers in their efforts to develop and validate new word space models. The +toolkit is available at {\small + \url{http://code.google.com/p/airhead-research/}}, which includes a wiki +containing detailed information on the algorithms, code documentation and +mailing list archives. +%% + +\section{Word Space Models} +\label{sec:sspace} + +Word space models are based on the contextual distribution in which a word +occurs. This approach has a long history in linguistics, starting with Firth +\shortcite{firth57synopsis} and Harris \shortcite{harris68mathematical}, the +latter of whom defined this approach as the Distributional Hypothesis: for two +words, their similarity in meaning is predicted by the similarity of the +distributions of their co-occurring words. Later models have expanded the +notion of co-occurrence but retain the premise that distributional similarity +can be used to extract meaningful relationships between words. + +\begin{figure*}[bt!f!p] + \center \includegraphics[width=1\textwidth]{figures/s-space-alg.eps} + \caption{A high-level depiction of common algorithmic steps that convert a + corpus into a word space} + \label{fig:algorithm} +\end{figure*} + +Word space algorithms consist of the same core algorithmic steps: word features +are extracted from a corpus and the distribution of these features is used as a +basis for semantic similarity. Figure \ref{fig:algorithm} illustrates the +shared algorithmic structure of all the approaches, which is divided into four +components: corpus processing, context selection, feature extraction and global +vector space operations. + +Corpus processing normalizes the input to create a more uniform set of features +on which the algorithm can work. Corpus processing techniques frequently +include stemming and filtering of stop words or low-frequency words. For +web-gathered corpora, these steps also include removal of non linguistic tokens, +such as html markup, or restricting documents to a single language. + +Context selection determines which tokens in a document may be considered for +features. Common approaches use a lexical distance, syntactic relation, or +document co-occurrence to define the context. The various decisions for +selecting the context accounts for many differences between otherwise similar +approaches. + +Feature extraction determines the dimensions of the vector space by selecting +which tokens in the context will count as features. Features are commonly word +co-occurrences, but more advanced models may perform a statistical analysis to +select only those features that best distinguish word meanings. Other models +approximate the full set of features to enable better scalability. + +Global vector space operations are applied to the entire space once the initial +word features have been computed. Common operations include altering feature +weights and dimensionality reduction. These operations are designed to improve +word similarity by changing the feature space itself. + +\section{The S-Space Framework} + +The S-Space framework is designed to be extensible, simple to use, and scalable. +We achieve these goals through the use of Java interfaces, reusable word space +related data structures, and support for multi-threading. Each word space +algorithm is designed to run as a stand alone program and also to be used as a +library class. + +\subsection{Reference Algorithms} + +The package provides reference implementations for twelve word space algorithms, +which are listed in Table \ref{tab:algorithms}. Each algorithm is implemented +in its own Java package, and all commonalities have been factored out into +reusable library classes. The algorithms implement the same Java interface, +which provides a consistent abstraction of the four processing stages. + +\begin{table}[tb] + \small + \begin{tabular}{l} + \toprule + \multicolumn{1}{c}{\bf Document-Based Models} \\ + LSA \cite{landauer97solution} \\ + ESA \cite{gabrilovich07computing} \\ + Vector Space Model \cite{salton75vector} \\ + + \midrule + \multicolumn{1}{c}{\bf Co-occurrence Models} \\ + HAL \cite{burgess97modeling} \\ + COALS \cite{rohde09improved} \\ + + \midrule + \multicolumn{1}{c}{\bf Approximation Models} \\ + Random Indexing \cite{sahlgren08permutations} \\ + Reflective Random Indexing \cite{cohen2009reflective} \\ + TRI \cite{jurgens09event} \\ + BEAGLE \cite{jones06high} \\ + Incremental Semantic Analysis \cite{baroni07isa} \\ + + \midrule + \multicolumn{1}{c}{\bf Word Sense Induction Models} \\ + Purandare and Pedersen \cite{purandare04word} \\ + HERMIT \cite{jurgens10improving} \\ + \bottomrule + \end{tabular} + \caption{Algorithms in the S-Space Package} + \label{tab:algorithms} +\end{table} + + +We divide the algorithms into four categories based on their structural +similarity: document-based, co-occurrence, approximation, and Word Sense +Induction (WSI) models. Document-based models divide a corpus into discrete +documents and construct the vector space from word frequencies in the documents. +The documents are defined independently of the words that appear in them. +Co-occurrence models build the vector space using the distribution of +co-occurring words in a context, which is typically defined as a region around a +word or paths rooted in a parse tree. The third category of models approximate +co-occurrence data rather than model it explicitly in order to achieve better +scalability for larger data sets. WSI models also use co-occurrence but also +attempt to discover distinct word senses while building the vector space. For +example, these algorithms might represent ``earth'' with two vectors based on +its meanings ``planet'' and ``dirt.'' + +\subsection{Data Structures and Utilities} + +The S-Space Package provides efficient implementations for matrices, vectors, +and specialized data structures such as multi-maps and tries. Implementations +are modeled after the {\tt \footnotesize java.util} library and offer concurrent +implementations when multi-threading is required. In addition, the libraries +provide support for converting between multiple matrix formats, enabling +interaction with external matrix-based programs. The package also provides +support for parsing different corpora formats, such as XML or email threads. + +\subsection{Global Operation Utilities} + +Many algorithms incorporate dimensionality reduction to smooth their feature +data, e.g.\ \cite{landauer97solution,rohde09improved}, or to improve efficiency, +e.g.\ \cite{sahlgren08permutations,jones06high}. The S-Space Package supports +two common techniques: the Singular Value Decomposition (SVD) and randomized +projections. All matrix data structures are designed to seamlessly integrate +with six SVD implementations for maximum portability, including +SVDLIBJ\footnote{\texttt{\scriptsize + http://bender.unibe.ch/svn/codemap/Archive/svdlibj/}} , a Java port of +SVDLIBC\footnote{\texttt{\scriptsize http://tedlab.mit.edu/\~dr/SVDLIBC/}}, a +scalable sparse SVD library. The package also provides a comprehensive library +for randomized projections, which project high-dimensional feature data into a +lower dimensional space. The library supports both integer-based projections +\cite{kanerva00random} and Gaussian-based \cite{jones06high}. + +The package supports common matrix transformations that have been applied to +word spaces: point wise mutual information \cite{lin98automatic}, term +frequency-inverse document frequency \cite{salton88term}, +and log entropy +\cite{landauer97solution}. + +\subsection{Measurements} + +The choice of similarity function for the vector space is the least standardized +across approaches. Typically the function is empirically chosen based on a +performance benchmark and different functions have been shown to provide +application specific benefits \cite{weeds04characterising}. +To facilitate exploration of the similarity function parameter space, the +S-Space Package provides support for multiple similarity functions: cosine +similarity, Euclidean distance, KL divergence, Jaccard Index, Pearson +product-moment correlation, Spearman's rank correlation, and Lin Similarity +\cite{lin98automatic} + +\subsection{Clustering} + +Clustering serves as a tool for building and refining word spaces. WSI +algorithms, e.g.\ \cite{purandare04word}, use clustering to discover the +different meanings of a word in a corpus. The S-Space Package provides bindings +for using the CLUTO clustering package\footnote{\texttt{\scriptsize + \url{http://glaros.dtc.umn.edu/gkhome/views/cluto}}}. In addition, the +package provides Java implementations of Hierarchical Agglomerative Clustering, +Spectral Clustering \cite{kannan04clusterings}, and the Gap Statistic +\cite{tibshirani00estimating}. + +\section{Benchmarks} +\label{sec:benchmarks} + +\begin{table*}[htb] + \center + \begin{threeparttable} + \begin{tabular}{l l r ccc r ccc } + \toprule + & & & \multicolumn{3}{c}{Word Choice} & & + \multicolumn{3}{c}{Word Association} \\ + \cmidrule{4-6} \cmidrule{8-10} + Algorithm & Corpus && TOEFL & ESL & RDWP & & R-G & WordSim353 & Deese \\ + \midrule + \midrule + BEAGLE & TASA && 46.03 & 35.56 & 46.99 && 0.431 & 0.342 & 0.235 \\ + COALS & TASA && 65.33 & \textbf{60.42} & \textbf{93.02} && 0.572 & 0.478 & \textbf{0.388} \\ + HAL & TASA && 44.00 & 20.83 & 50.00 && 0.173 & 0.180 & 0.318 \\ + HAL & Wiki && 50.00 & 31.11 & 43.44 && 0.261 & 0.195 & 0.042 \\ + ISA & TASA && 41.33 & 18.75 & 33.72 && 0.245 & 0.150 & 0.286 \\ + LSA & TASA && 56.00\tnote{a} & 50.00 & 45.83 && 0.652 & 0.519 & 0.349 \\ + LSA & Wiki && 60.76 & 54.17 & 59.20 && \textbf{0.681} & \textbf{0.614} & 0.206 \\ + P\&P & TASA && 34.67 & 20.83 & 31.39 && 0.088 & -0.036 & 0.216 \\ + RI & TASA && 42.67 & 27.08 & 34.88 && 0.224 & 0.201 & 0.211 \\ + RI & Wiki && \textbf{68.35} & 31.25 & 40.80 && 0.226 & 0.315 & 0.090 \\ + RI $+$ Perm.\tnote{b}& TASA && 52.00 & 33.33 & 31.39 && 0.137 & 0.260 & 0.268 \\ + RRI & TASA && 36.00 & 22.92 & 34.88 && 0.088 & 0.138 & 0.109 \\ + VSM & TASA && 61.33 & 52.08 & 84.88 && 0.496 & 0.396 & 0.200 \\ + \bottomrule + \end{tabular} + \begin{tablenotes} + \item[a] {\footnotesize Landauer et al.\ \shortcite{landauer97solution} + report a score of 64.4 for this test, while Rohde et + al. \shortcite{rohde09improved} report a score of 53.4.} + \item[b] {\footnotesize $+$ Perm indicates that permutations were used with + Random Indexing, as described in \cite{sahlgren08permutations}} + \end{tablenotes} + \end{threeparttable} + \caption{A comparison of the implemented algorithms on common evaluation + benchmarks} + \label{tab:evaluation} +\end{table*} + +Word space benchmarks assess the semantic content of the space through analyzing +the geometric properties of the space itself. Currently used benchmarks assess +the semantics by inspecting the representational similarity of word pairs. Two +types of benchmarks are commonly used: word choice tests and association tests. +% +The S-Space Package supports six tests, and has an easily extensible model for +adding new tests. + +\subsection{Word Choice} + +Word choice tests provide a target word and a list of options, one of which has +the desired relation to the target. Word space models solve these tests by +selecting the option whose representation is most similar. Three word choice +benchmarks that measure synonymy are supported. + +The first test is the widely-reported Test of English as a Foreign Language +(TOEFL) synonym test from \cite{landauer98introduction}, which consists of 80 +multiple-choice questions with four options. The second test comes from the +English as a Second Language (ESL) exam and consists of 50 question with four +choices \cite{turney01mining}. The third consists of 200 questions from the +Canadian Reader's Digest Word Power (RDWP) \cite{jarmasz03rogets}, which unlike +the previous two tests, allows the target and options to be multi-word phrases. + +\subsection{Word Association} + +Word association tests measure the semantic relatedness of two words by +comparing word space similarity with human judgements. Frequently, these tests +measure synonymy; however, other types of word relations such as antonymy +(``hot'' and ``cold'') or functional relatedness (``doctor'' and ``hospital'') +are also possible. The S-Space Package supports three association tests. + +The first test uses data gathered by Rubenstein and Goodneough +\shortcite{rubenstein65contextual}. To measure word similarity, word similarity +scores of 51 human reviewers were gathered a set of 65 noun pairs, scored on a +scale of 0 to 4. The ratings are then correlated with word space similarity +scores. + +Finkelstein et al.\ \shortcite{finkelstein02placing} test for relatedness. 353 +word pairs were rated by either 13 or 16 subjects on a 0 to 10 scale for how +related the words are. This test is notably more challenging for word space +models because human ratings are not tied to a specific semantic relation. + +The third benchmark considers the antonym association. Deese +\shortcite{deese64associative} introduced 39 antonym pairs that Greffenstette +\shortcite{grefenstette92finding} used to assess whether a word space modeled +the antonymy relationship. We quantify this relationship by measuring the +similarity rank of each word in an antonym pair, $w_1,w_2$, i.e.\ $w_2$ is the +$k^{th}$ most-similar word to $w_1$ in the vector space. The antonym score is +calculated as $\frac{2}{rank_{w_1}(w_2) + rank_{w_2}(w_1)}$. The score ranges +from $[0,1]$, where $1$ indicates that the most similar neighbors in the space are +antonyms. We report the mean score for all 39 antonyms. + +\section{Algorithm Analysis} + +The content of a word space is fundamentally dependent upon the corpus used to +construct it. Moreover, algorithms which use operations such as the SVD have a +limit to the corpora sizes they can process. We therefore highlight the +differences in performance using two corpora. TASA is a collection of 44,486 +topical essays introduced in \cite{landauer97solution}. The second corpus is +built from a Nov. 11, 2009 Wikipedia snapshot, and filtered to contain only +articles with more than 1000 words. The resulting corpus consists of +387,082 documents and 917 million tokens. + +Table \ref{tab:evaluation} reports the scores of reference algorithms on the six +benchmarks using cosine similarity. The variation in scoring illustrates that +different algorithms are more effective at capturing certain semantic relations. +We note that scores are likely to change for different parameter configurations +of the same algorithm, e.g.\ token filtering or changing the number of +dimensions. + +\begin{figure}[tb] + \center + \includegraphics[angle=270,width=.46\textwidth]{figures/timing.eps} + \caption{Processing time across different corpus sizes for a word space with + the 100,000 most frequent words} + \label{fig:sspace_timing} +\end{figure} + +\begin{figure}[tb] + \center + \includegraphics[angle=270,width=.46\textwidth]{figures/threading.eps} + \caption{Run time improvement as a factor of increasing the number of + threads} + \label{fig:sspace_threads} +\end{figure} + + +As a second analysis, we report the efficiency of reference implementations by +varying the corpus size and number of threads. Figure \ref{fig:sspace_timing} +reports the total amount of time each algorithm needs for processing +increasingly larger segments of a web-gathered corpus when using 8 threads. In +all cases, only the top 100,000 words were counted as features. Figure +\ref{fig:sspace_threads} reports run time improvements due to multi-threading on +the TASA corpus. + +Algorithm efficiency is determined by three factors: contention on global +statistics, contention on disk I/O, and memory limitations. Multi-threading +benefits increase proportionally to the amount of work done per context. Memory +limitations account for the largest efficiency constraint, especially as the +corpus size and number of features grow. Several algorithms lack data points +for larger corpora and show a sharp increase in running time in Figure +\ref{fig:sspace_timing}, reflecting the point at which the models no longer fit +into 8GB of memory. + +\section{Future Work and Conclusion} + +We have described a framework for developing and evaluating word space +algorithms. Many well known algorithms are already provided as part of the +framework as reference implementations for researches in distributional +semantics. We have shown that the provided algorithms and libraries scale +appropriately. Last, we motivate further research by illustrating the +significant performance differences of the algorithms on six benchmarks. + +Future work will be focused on providing support for syntactic features, +including dependency parsing as described by \cite{pado07dependency}, reference +implementations of algorithms that use this information, more non-linear +dimensionality reduction techniques, and more advanced clustering algorithms. + +\bibliographystyle{acl} +\bibliography{acl-sspace-paper} + +\end{document} diff --git a/papers/2010_acl_systems_sspace/acl.bst b/papers/2010_acl_systems_sspace/acl.bst new file mode 100644 index 00000000..b95ec040 --- /dev/null +++ b/papers/2010_acl_systems_sspace/acl.bst @@ -0,0 +1,1322 @@ + +% BibTeX `acl' style file for BibTeX version 0.99c, LaTeX version 2.09 +% This version was made by modifying `aaai-named' format based on the master +% file by Oren Patashnik (PATASHNIK@SCORE.STANFORD.EDU) + +% Copyright (C) 1985, all rights reserved. +% Modifications Copyright 1988, Peter F. Patel-Schneider +% Further modifictions by Stuart Shieber, 1991, and Fernando Pereira, 1992. +% Copying of this file is authorized only if either +% (1) you make absolutely no changes to your copy, including name, or +% (2) if you do make changes, you name it something other than +% btxbst.doc, plain.bst, unsrt.bst, alpha.bst, and abbrv.bst. +% This restriction helps ensure that all standard styles are identical. + +% There are undoubtably bugs in this style. If you make bug fixes, +% improvements, etc. please let me know. My e-mail address is: +% pfps@spar.slb.com + +% Citation format: [author-last-name, year] +% [author-last-name and author-last-name, year] +% [author-last-name {\em et al.}, year] +% +% Reference list ordering: alphabetical by author or whatever passes +% for author in the absence of one. +% +% This BibTeX style has support for short (year only) citations. This +% is done by having the citations actually look like +% \citename{name-info, }year +% The LaTeX style has to have the following +% \let\@internalcite\cite +% \def\cite{\def\citename##1{##1}\@internalcite} +% \def\shortcite{\def\citename##1{}\@internalcite} +% \def\@biblabel#1{\def\citename##1{##1}[#1]\hfill} +% which makes \shortcite the macro for short citations. + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% Changes made by SMS for thesis style +% no emphasis on "et al." +% "Ph.D." includes periods (not "PhD") +% moved year to immediately after author's name +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +ENTRY + { address + author + booktitle + chapter + edition + editor + howpublished + institution + journal + key + month + note + number + organization + pages + publisher + school + series + title + type + volume + year + } + {} + { label extra.label sort.label } + +INTEGERS { output.state before.all mid.sentence after.sentence after.block } + +FUNCTION {init.state.consts} +{ #0 'before.all := + #1 'mid.sentence := + #2 'after.sentence := + #3 'after.block := +} + +STRINGS { s t } + +FUNCTION {output.nonnull} +{ 's := + output.state mid.sentence = + { ", " * write$ } + { output.state after.block = + { add.period$ write$ + newline$ + "\newblock " write$ + } + { output.state before.all = + 'write$ + { add.period$ " " * write$ } + if$ + } + if$ + mid.sentence 'output.state := + } + if$ + s +} + +FUNCTION {output} +{ duplicate$ empty$ + 'pop$ + 'output.nonnull + if$ +} + +FUNCTION {output.check} +{ 't := + duplicate$ empty$ + { pop$ "empty " t * " in " * cite$ * warning$ } + 'output.nonnull + if$ +} + +FUNCTION {output.bibitem} +{ newline$ + + "\bibitem[" write$ + label write$ + "]{" write$ + + cite$ write$ + "}" write$ + newline$ + "" + before.all 'output.state := +} + +FUNCTION {fin.entry} +{ add.period$ + write$ + newline$ +} + +FUNCTION {new.block} +{ output.state before.all = + 'skip$ + { after.block 'output.state := } + if$ +} + +FUNCTION {new.sentence} +{ output.state after.block = + 'skip$ + { output.state before.all = + 'skip$ + { after.sentence 'output.state := } + if$ + } + if$ +} + +FUNCTION {not} +{ { #0 } + { #1 } + if$ +} + +FUNCTION {and} +{ 'skip$ + { pop$ #0 } + if$ +} + +FUNCTION {or} +{ { pop$ #1 } + 'skip$ + if$ +} + +FUNCTION {new.block.checka} +{ empty$ + 'skip$ + 'new.block + if$ +} + +FUNCTION {new.block.checkb} +{ empty$ + swap$ empty$ + and + 'skip$ + 'new.block + if$ +} + +FUNCTION {new.sentence.checka} +{ empty$ + 'skip$ + 'new.sentence + if$ +} + +FUNCTION {new.sentence.checkb} +{ empty$ + swap$ empty$ + and + 'skip$ + 'new.sentence + if$ +} + +FUNCTION {field.or.null} +{ duplicate$ empty$ + { pop$ "" } + 'skip$ + if$ +} + +FUNCTION {emphasize} +{ duplicate$ empty$ + { pop$ "" } + { "{\em " swap$ * "}" * } + if$ +} + +INTEGERS { nameptr namesleft numnames } + +FUNCTION {format.names} +{ 's := + #1 'nameptr := + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + + { s nameptr "{ff~}{vv~}{ll}{, jj}" format.name$ 't := + + nameptr #1 > + { namesleft #1 > + { ", " * t * } + { numnames #2 > + { "," * } + 'skip$ + if$ + t "others" = + { " et~al." * } + { " and " * t * } + if$ + } + if$ + } + 't + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {format.authors} +{ author empty$ + { "" } + { author format.names } + if$ +} + +FUNCTION {format.editors} +{ editor empty$ + { "" } + { editor format.names + editor num.names$ #1 > + { ", editors" * } + { ", editor" * } + if$ + } + if$ +} + +FUNCTION {format.title} +{ title empty$ + { "" } + + { title "t" change.case$ } + + if$ +} + +FUNCTION {n.dashify} +{ 't := + "" + { t empty$ not } + { t #1 #1 substring$ "-" = + { t #1 #2 substring$ "--" = not + { "--" * + t #2 global.max$ substring$ 't := + } + { { t #1 #1 substring$ "-" = } + { "-" * + t #2 global.max$ substring$ 't := + } + while$ + } + if$ + } + { t #1 #1 substring$ * + t #2 global.max$ substring$ 't := + } + if$ + } + while$ +} + +FUNCTION {format.date} +{ year empty$ + { month empty$ + { "" } + { "there's a month but no year in " cite$ * warning$ + month + } + if$ + } + { month empty$ + { "" } + { month } + if$ + } + if$ +} + +FUNCTION {format.btitle} +{ title emphasize +} + +FUNCTION {tie.or.space.connect} +{ duplicate$ text.length$ #3 < + { "~" } + { " " } + if$ + swap$ * * +} + +FUNCTION {either.or.check} +{ empty$ + 'pop$ + { "can't use both " swap$ * " fields in " * cite$ * warning$ } + if$ +} + +FUNCTION {format.bvolume} +{ volume empty$ + { "" } + { "volume" volume tie.or.space.connect + series empty$ + 'skip$ + { " of " * series emphasize * } + if$ + "volume and number" number either.or.check + } + if$ +} + +FUNCTION {format.number.series} +{ volume empty$ + { number empty$ + { series field.or.null } + { output.state mid.sentence = + { "number" } + { "Number" } + if$ + number tie.or.space.connect + series empty$ + { "there's a number but no series in " cite$ * warning$ } + { " in " * series * } + if$ + } + if$ + } + { "" } + if$ +} + +FUNCTION {format.edition} +{ edition empty$ + { "" } + { output.state mid.sentence = + { edition "l" change.case$ " edition" * } + { edition "t" change.case$ " edition" * } + if$ + } + if$ +} + +INTEGERS { multiresult } + +FUNCTION {multi.page.check} +{ 't := + #0 'multiresult := + { multiresult not + t empty$ not + and + } + { t #1 #1 substring$ + duplicate$ "-" = + swap$ duplicate$ "," = + swap$ "+" = + or or + { #1 'multiresult := } + { t #2 global.max$ substring$ 't := } + if$ + } + while$ + multiresult +} + +FUNCTION {format.pages} +{ pages empty$ + { "" } + { pages multi.page.check + { "pages" pages n.dashify tie.or.space.connect } + { "page" pages tie.or.space.connect } + if$ + } + if$ +} + +FUNCTION {format.year.label} +{ year extra.label * +} + +FUNCTION {format.vol.num.pages} +{ volume field.or.null + number empty$ + 'skip$ + { "(" number * ")" * * + volume empty$ + { "there's a number but no volume in " cite$ * warning$ } + 'skip$ + if$ + } + if$ + pages empty$ + 'skip$ + { duplicate$ empty$ + { pop$ format.pages } + { ":" * pages n.dashify * } + if$ + } + if$ +} + +FUNCTION {format.chapter.pages} +{ chapter empty$ + 'format.pages + { type empty$ + { "chapter" } + { type "l" change.case$ } + if$ + chapter tie.or.space.connect + pages empty$ + 'skip$ + { ", " * format.pages * } + if$ + } + if$ +} + +FUNCTION {format.in.ed.booktitle} +{ booktitle empty$ + { "" } + { editor empty$ + { "In " booktitle emphasize * } + { "In " format.editors * ", " * booktitle emphasize * } + if$ + } + if$ +} + +FUNCTION {empty.misc.check} +{ author empty$ title empty$ howpublished empty$ + month empty$ year empty$ note empty$ + and and and and and + + key empty$ not and + + { "all relevant fields are empty in " cite$ * warning$ } + 'skip$ + if$ +} + +FUNCTION {format.thesis.type} +{ type empty$ + 'skip$ + { pop$ + type "t" change.case$ + } + if$ +} + +FUNCTION {format.tr.number} +{ type empty$ + { "Technical Report" } + 'type + if$ + number empty$ + { "t" change.case$ } + { number tie.or.space.connect } + if$ +} + +FUNCTION {format.article.crossref} +{ key empty$ + { journal empty$ + { "need key or journal for " cite$ * " to crossref " * crossref * + warning$ + "" + } + { "In {\em " journal * "\/}" * } + if$ + } + { "In " key * } + if$ + " \cite{" * crossref * "}" * +} + +FUNCTION {format.crossref.editor} +{ editor #1 "{vv~}{ll}" format.name$ + editor num.names$ duplicate$ + #2 > + { pop$ " et~al." * } + { #2 < + 'skip$ + { editor #2 "{ff }{vv }{ll}{ jj}" format.name$ "others" = + { " et~al." * } + { " and " * editor #2 "{vv~}{ll}" format.name$ * } + if$ + } + if$ + } + if$ +} + +FUNCTION {format.book.crossref} +{ volume empty$ + { "empty volume in " cite$ * "'s crossref of " * crossref * warning$ + "In " + } + { "Volume" volume tie.or.space.connect + " of " * + } + if$ + editor empty$ + editor field.or.null author field.or.null = + or + { key empty$ + { series empty$ + { "need editor, key, or series for " cite$ * " to crossref " * + crossref * warning$ + "" * + } + { "{\em " * series * "\/}" * } + if$ + } + { key * } + if$ + } + { format.crossref.editor * } + if$ + " \cite{" * crossref * "}" * +} + +FUNCTION {format.incoll.inproc.crossref} +{ editor empty$ + editor field.or.null author field.or.null = + or + { key empty$ + { booktitle empty$ + { "need editor, key, or booktitle for " cite$ * " to crossref " * + crossref * warning$ + "" + } + { "In {\em " booktitle * "\/}" * } + if$ + } + { "In " key * } + if$ + } + { "In " format.crossref.editor * } + if$ + " \cite{" * crossref * "}" * +} + +FUNCTION {article} +{ output.bibitem + format.authors "author" output.check + new.block + format.year.label "year" output.check + new.block + format.title "title" output.check + new.block + crossref missing$ + { journal emphasize "journal" output.check + format.vol.num.pages output + format.date output + } + { format.article.crossref output.nonnull + format.pages output + } + if$ + new.block + note output + fin.entry +} + +FUNCTION {book} +{ output.bibitem + author empty$ + { format.editors "author and editor" output.check } + { format.authors output.nonnull + crossref missing$ + { "author and editor" editor either.or.check } + 'skip$ + if$ + } + if$ + new.block + format.year.label "year" output.check + new.block + format.btitle "title" output.check + crossref missing$ + { format.bvolume output + new.block + format.number.series output + new.sentence + publisher "publisher" output.check + address output + } + { new.block + format.book.crossref output.nonnull + } + if$ + format.edition output + format.date output + new.block + note output + fin.entry +} + +FUNCTION {booklet} +{ output.bibitem + format.authors output + new.block + format.year.label "year" output.check + new.block + format.title "title" output.check + howpublished address new.block.checkb + howpublished output + address output + format.date output + new.block + note output + fin.entry +} + +FUNCTION {inbook} +{ output.bibitem + author empty$ + { format.editors "author and editor" output.check } + { format.authors output.nonnull + crossref missing$ + { "author and editor" editor either.or.check } + 'skip$ + if$ + } + if$ + format.year.label "year" output.check + new.block + new.block + format.btitle "title" output.check + crossref missing$ + { format.bvolume output + format.chapter.pages "chapter and pages" output.check + new.block + format.number.series output + new.sentence + publisher "publisher" output.check + address output + } + { format.chapter.pages "chapter and pages" output.check + new.block + format.book.crossref output.nonnull + } + if$ + format.edition output + format.date output + new.block + note output + fin.entry +} + +FUNCTION {incollection} +{ output.bibitem + format.authors "author" output.check + new.block + format.year.label "year" output.check + new.block + format.title "title" output.check + new.block + crossref missing$ + { format.in.ed.booktitle "booktitle" output.check + format.bvolume output + format.number.series output + format.chapter.pages output + new.sentence + publisher "publisher" output.check + address output + format.edition output + format.date output + } + { format.incoll.inproc.crossref output.nonnull + format.chapter.pages output + } + if$ + new.block + note output + fin.entry +} + +FUNCTION {inproceedings} +{ output.bibitem + format.authors "author" output.check + new.block + format.year.label "year" output.check + new.block + format.title "title" output.check + new.block + crossref missing$ + { format.in.ed.booktitle "booktitle" output.check + format.bvolume output + format.number.series output + format.pages output + address empty$ + { organization publisher new.sentence.checkb + organization output + publisher output + format.date output + } + { address output.nonnull + format.date output + new.sentence + organization output + publisher output + } + if$ + } + { format.incoll.inproc.crossref output.nonnull + format.pages output + } + if$ + new.block + note output + fin.entry +} + +FUNCTION {conference} { inproceedings } + +FUNCTION {manual} +{ output.bibitem + author empty$ + { organization empty$ + 'skip$ + { organization output.nonnull + address output + } + if$ + } + { format.authors output.nonnull } + if$ + format.year.label "year" output.check + new.block + new.block + format.btitle "title" output.check + author empty$ + { organization empty$ + { address new.block.checka + address output + } + 'skip$ + if$ + } + { organization address new.block.checkb + organization output + address output + } + if$ + format.edition output + format.date output + new.block + note output + fin.entry +} + +FUNCTION {mastersthesis} +{ output.bibitem + format.authors "author" output.check + new.block + format.year.label "year" output.check + new.block + format.title "title" output.check + new.block + "Master's thesis" format.thesis.type output.nonnull + school "school" output.check + address output + format.date output + new.block + note output + fin.entry +} + +FUNCTION {misc} +{ output.bibitem + format.authors output + new.block + format.year.label output + new.block + title howpublished new.block.checkb + format.title output + howpublished new.block.checka + howpublished output + format.date output + new.block + note output + fin.entry + empty.misc.check +} + +FUNCTION {phdthesis} +{ output.bibitem + format.authors "author" output.check + new.block + format.year.label "year" output.check + new.block + format.btitle "title" output.check + new.block + "{Ph.D.} thesis" format.thesis.type output.nonnull + school "school" output.check + address output + format.date output + new.block + note output + fin.entry +} + +FUNCTION {proceedings} +{ output.bibitem + editor empty$ + { organization output } + { format.editors output.nonnull } + if$ + new.block + format.year.label "year" output.check + new.block + format.btitle "title" output.check + format.bvolume output + format.number.series output + address empty$ + { editor empty$ + { publisher new.sentence.checka } + { organization publisher new.sentence.checkb + organization output + } + if$ + publisher output + format.date output + } + { address output.nonnull + format.date output + new.sentence + editor empty$ + 'skip$ + { organization output } + if$ + publisher output + } + if$ + new.block + note output + fin.entry +} + +FUNCTION {techreport} +{ output.bibitem + format.authors "author" output.check + new.block + format.year.label "year" output.check + new.block + format.title "title" output.check + new.block + format.tr.number output.nonnull + institution "institution" output.check + address output + format.date output + new.block + note output + fin.entry +} + +FUNCTION {unpublished} +{ output.bibitem + format.authors "author" output.check + new.block + format.year.label "year" output.check + new.block + format.title "title" output.check + new.block + note "note" output.check + format.date output + fin.entry +} + +FUNCTION {default.type} { misc } + +MACRO {jan} {"January"} + +MACRO {feb} {"February"} + +MACRO {mar} {"March"} + +MACRO {apr} {"April"} + +MACRO {may} {"May"} + +MACRO {jun} {"June"} + +MACRO {jul} {"July"} + +MACRO {aug} {"August"} + +MACRO {sep} {"September"} + +MACRO {oct} {"October"} + +MACRO {nov} {"November"} + +MACRO {dec} {"December"} + +MACRO {acmcs} {"ACM Computing Surveys"} + +MACRO {acta} {"Acta Informatica"} + +MACRO {cacm} {"Communications of the ACM"} + +MACRO {ibmjrd} {"IBM Journal of Research and Development"} + +MACRO {ibmsj} {"IBM Systems Journal"} + +MACRO {ieeese} {"IEEE Transactions on Software Engineering"} + +MACRO {ieeetc} {"IEEE Transactions on Computers"} + +MACRO {ieeetcad} + {"IEEE Transactions on Computer-Aided Design of Integrated Circuits"} + +MACRO {ipl} {"Information Processing Letters"} + +MACRO {jacm} {"Journal of the ACM"} + +MACRO {jcss} {"Journal of Computer and System Sciences"} + +MACRO {scp} {"Science of Computer Programming"} + +MACRO {sicomp} {"SIAM Journal on Computing"} + +MACRO {tocs} {"ACM Transactions on Computer Systems"} + +MACRO {tods} {"ACM Transactions on Database Systems"} + +MACRO {tog} {"ACM Transactions on Graphics"} + +MACRO {toms} {"ACM Transactions on Mathematical Software"} + +MACRO {toois} {"ACM Transactions on Office Information Systems"} + +MACRO {toplas} {"ACM Transactions on Programming Languages and Systems"} + +MACRO {tcs} {"Theoretical Computer Science"} + +READ + +FUNCTION {sortify} +{ purify$ + "l" change.case$ +} + +INTEGERS { len } + +FUNCTION {chop.word} +{ 's := + 'len := + s #1 len substring$ = + { s len #1 + global.max$ substring$ } + 's + if$ +} + +INTEGERS { et.al.char.used } + +FUNCTION {initialize.et.al.char.used} +{ #0 'et.al.char.used := +} + +EXECUTE {initialize.et.al.char.used} + +FUNCTION {format.lab.names} +{ 's := + s num.names$ 'numnames := + + numnames #1 = + { s #1 "{vv }{ll}" format.name$ } + { numnames #2 = + { s #1 "{vv }{ll }and " format.name$ s #2 "{vv }{ll}" format.name$ * + } + { s #1 "{vv }{ll }\bgroup et al.\egroup " format.name$ } + if$ + } + if$ + +} + +FUNCTION {author.key.label} +{ author empty$ + { key empty$ + + { cite$ #1 #3 substring$ } + + { key #3 text.prefix$ } + if$ + } + { author format.lab.names } + if$ +} + +FUNCTION {author.editor.key.label} +{ author empty$ + { editor empty$ + { key empty$ + + { cite$ #1 #3 substring$ } + + { key #3 text.prefix$ } + if$ + } + { editor format.lab.names } + if$ + } + { author format.lab.names } + if$ +} + +FUNCTION {author.key.organization.label} +{ author empty$ + { key empty$ + { organization empty$ + + { cite$ #1 #3 substring$ } + + { "The " #4 organization chop.word #3 text.prefix$ } + if$ + } + { key #3 text.prefix$ } + if$ + } + { author format.lab.names } + if$ +} + +FUNCTION {editor.key.organization.label} +{ editor empty$ + { key empty$ + { organization empty$ + + { cite$ #1 #3 substring$ } + + { "The " #4 organization chop.word #3 text.prefix$ } + if$ + } + { key #3 text.prefix$ } + if$ + } + { editor format.lab.names } + if$ +} + +FUNCTION {calc.label} +{ type$ "book" = + type$ "inbook" = + or + 'author.editor.key.label + { type$ "proceedings" = + 'editor.key.organization.label + { type$ "manual" = + 'author.key.organization.label + 'author.key.label + if$ + } + if$ + } + if$ + duplicate$ + + "\protect\citename{" swap$ * "}" * + year field.or.null purify$ * + 'label := + year field.or.null purify$ * + + sortify 'sort.label := +} + +FUNCTION {sort.format.names} +{ 's := + #1 'nameptr := + "" + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + { nameptr #1 > + { " " * } + 'skip$ + if$ + + s nameptr "{vv{ } }{ll{ }}{ ff{ }}{ jj{ }}" format.name$ 't := + + nameptr numnames = t "others" = and + { "et al" * } + { t sortify * } + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {sort.format.title} +{ 't := + "A " #2 + "An " #3 + "The " #4 t chop.word + chop.word + chop.word + sortify + #1 global.max$ substring$ +} + +FUNCTION {author.sort} +{ author empty$ + { key empty$ + { "to sort, need author or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { author sort.format.names } + if$ +} + +FUNCTION {author.editor.sort} +{ author empty$ + { editor empty$ + { key empty$ + { "to sort, need author, editor, or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { editor sort.format.names } + if$ + } + { author sort.format.names } + if$ +} + +FUNCTION {author.organization.sort} +{ author empty$ + { organization empty$ + { key empty$ + { "to sort, need author, organization, or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { "The " #4 organization chop.word sortify } + if$ + } + { author sort.format.names } + if$ +} + +FUNCTION {editor.organization.sort} +{ editor empty$ + { organization empty$ + { key empty$ + { "to sort, need editor, organization, or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { "The " #4 organization chop.word sortify } + if$ + } + { editor sort.format.names } + if$ +} + +FUNCTION {presort} + +{ calc.label + sort.label + " " + * + type$ "book" = + + type$ "inbook" = + or + 'author.editor.sort + { type$ "proceedings" = + 'editor.organization.sort + { type$ "manual" = + 'author.organization.sort + 'author.sort + if$ + } + if$ + } + if$ + + * + + " " + * + year field.or.null sortify + * + " " + * + title field.or.null + sort.format.title + * + #1 entry.max$ substring$ + 'sort.key$ := +} + +ITERATE {presort} + +SORT + +STRINGS { longest.label last.sort.label next.extra } + +INTEGERS { longest.label.width last.extra.num } + +FUNCTION {initialize.longest.label} +{ "" 'longest.label := + #0 int.to.chr$ 'last.sort.label := + "" 'next.extra := + #0 'longest.label.width := + #0 'last.extra.num := +} + +FUNCTION {forward.pass} +{ last.sort.label sort.label = + { last.extra.num #1 + 'last.extra.num := + last.extra.num int.to.chr$ 'extra.label := + } + { "a" chr.to.int$ 'last.extra.num := + "" 'extra.label := + sort.label 'last.sort.label := + } + if$ +} + +FUNCTION {reverse.pass} +{ next.extra "b" = + { "a" 'extra.label := } + 'skip$ + if$ + label extra.label * 'label := + label width$ longest.label.width > + { label 'longest.label := + label width$ 'longest.label.width := + } + 'skip$ + if$ + extra.label 'next.extra := +} + +EXECUTE {initialize.longest.label} + +ITERATE {forward.pass} + +REVERSE {reverse.pass} + +FUNCTION {begin.bib} + +{ et.al.char.used + { "\newcommand{\etalchar}[1]{$^{#1}$}" write$ newline$ } + 'skip$ + if$ + preamble$ empty$ + + 'skip$ + { preamble$ write$ newline$ } + if$ + + "\begin{thebibliography}{" "}" * write$ newline$ + +} + +EXECUTE {begin.bib} + +EXECUTE {init.state.consts} + +ITERATE {call.type$} + +FUNCTION {end.bib} +{ newline$ + "\end{thebibliography}" write$ newline$ +} + +EXECUTE {end.bib} + diff --git a/papers/2010_acl_systems_sspace/acl2010.pdf b/papers/2010_acl_systems_sspace/acl2010.pdf new file mode 100644 index 00000000..4966a7e7 Binary files /dev/null and b/papers/2010_acl_systems_sspace/acl2010.pdf differ diff --git a/papers/2010_acl_systems_sspace/acl2010.sty b/papers/2010_acl_systems_sspace/acl2010.sty new file mode 100644 index 00000000..e580ae8e --- /dev/null +++ b/papers/2010_acl_systems_sspace/acl2010.sty @@ -0,0 +1,370 @@ +% File acl2010.sty +% same as -- +% File acl-ijcnlp2009.sty +% same as -- +% File eacl2006.sty +% September 19, 2005 +% Contact: e.agirre@ehu.es or Sergi.Balari@uab.es + +% This is the LaTeX style file for EACL 2006. It is nearly identical to the +% style files for ACL2005, ACL 2002, ACL 2001, ACL 2000, EACL 95 and EACL +% 99. +% +% Changes made include: adapt layout to A4 and centimeters, widden abstract + +% This is the LaTeX style file for ACL 2000. It is nearly identical to the +% style files for EACL 95 and EACL 99. Minor changes include editing the +% instructions to reflect use of \documentclass rather than \documentstyle +% and removing the white space before the title on the first page +% -- John Chen, June 29, 2000 + +% To convert from submissions prepared using the style file aclsub.sty +% prepared for the ACL 2000 conference, proceed as follows: +% 1) Remove submission-specific information: \whichsession, \id, +% \wordcount, \otherconferences, \area, \keywords +% 2) \summary should be removed. The summary material should come +% after \maketitle and should be in the ``abstract'' environment +% 3) Check all citations. This style should handle citations correctly +% and also allows multiple citations separated by semicolons. +% 4) Check figures and examples. Because the final format is double- +% column, some adjustments may have to be made to fit text in the column +% or to choose full-width (\figure*} figures. +% 5) Change the style reference from aclsub to acl2000, and be sure +% this style file is in your TeX search path + + +% This is the LaTeX style file for EACL-95. It is identical to the +% style file for ANLP '94 except that the margins are adjusted for A4 +% paper. -- abney 13 Dec 94 + +% The ANLP '94 style file is a slightly modified +% version of the style used for AAAI and IJCAI, using some changes +% prepared by Fernando Pereira and others and some minor changes +% by Paul Jacobs. + +% Papers prepared using the aclsub.sty file and acl.bst bibtex style +% should be easily converted to final format using this style. +% (1) Submission information (\wordcount, \subject, and \makeidpage) +% should be removed. +% (2) \summary should be removed. The summary material should come +% after \maketitle and should be in the ``abstract'' environment +% (between \begin{abstract} and \end{abstract}). +% (3) Check all citations. This style should handle citations correctly +% and also allows multiple citations separated by semicolons. +% (4) Check figures and examples. Because the final format is double- +% column, some adjustments may have to be made to fit text in the column +% or to choose full-width (\figure*} figures. + +% Place this in a file called aclap.sty in the TeX search path. +% (Placing it in the same directory as the paper should also work.) + +% Prepared by Peter F. Patel-Schneider, liberally using the ideas of +% other style hackers, including Barbara Beeton. +% This style is NOT guaranteed to work. It is provided in the hope +% that it will make the preparation of papers easier. +% +% There are undoubtably bugs in this style. If you make bug fixes, +% improvements, etc. please let me know. My e-mail address is: +% pfps@research.att.com + +% Papers are to be prepared using the ``acl'' bibliography style, +% as follows: +% \documentclass[11pt]{article} +% \usepackage{acl2000} +% \title{Title} +% \author{Author 1 \and Author 2 \\ Address line \\ Address line \And +% Author 3 \\ Address line \\ Address line} +% \begin{document} +% ... +% \bibliography{bibliography-file} +% \bibliographystyle{acl} +% \end{document} + +% Author information can be set in various styles: +% For several authors from the same institution: +% \author{Author 1 \and ... \and Author n \\ +% Address line \\ ... \\ Address line} +% if the names do not fit well on one line use +% Author 1 \\ {\bf Author 2} \\ ... \\ {\bf Author n} \\ +% For authors from different institutions: +% \author{Author 1 \\ Address line \\ ... \\ Address line +% \And ... \And +% Author n \\ Address line \\ ... \\ Address line} +% To start a seperate ``row'' of authors use \AND, as in +% \author{Author 1 \\ Address line \\ ... \\ Address line +% \AND +% Author 2 \\ Address line \\ ... \\ Address line \And +% Author 3 \\ Address line \\ ... \\ Address line} + +% If the title and author information does not fit in the area allocated, +% place \setlength\titlebox{} right after +% \usepackage{acl2000} +% where can be something larger than 2.25in + +% \typeout{Conference Style for ACL 2000 -- released June 20, 2000} +\typeout{Conference Style for ACL 2005 -- released Octobe 11, 2004} + +% NOTE: Some laser printers have a serious problem printing TeX output. +% These printing devices, commonly known as ``write-white'' laser +% printers, tend to make characters too light. To get around this +% problem, a darker set of fonts must be created for these devices. +% + +%% % Physical page layout - slightly modified from IJCAI by pj +%% \setlength\topmargin{0.0in} \setlength\oddsidemargin{-0.0in} +%% \setlength\textheight{9.0in} \setlength\textwidth{6.5in} +%% \setlength\columnsep{0.2in} +%% \newlength\titlebox +%% \setlength\titlebox{2.25in} +%% \setlength\headheight{0pt} \setlength\headsep{0pt} +%% %\setlength\footheight{0pt} +%% \setlength\footskip{0pt} +%% \thispagestyle{empty} \pagestyle{empty} +%% \flushbottom \twocolumn \sloppy + +%% Original A4 version of page layout +%% \setlength\topmargin{-0.45cm} % changed by Rz -1.4 +%% \setlength\oddsidemargin{.8mm} % was -0cm, changed by Rz +%% \setlength\textheight{23.5cm} +%% \setlength\textwidth{15.8cm} +%% \setlength\columnsep{0.6cm} +%% \newlength\titlebox +%% \setlength\titlebox{2.00in} +%% \setlength\headheight{5pt} +%% \setlength\headsep{0pt} +%% \setlength\footheight{0pt} +%% \setlength\footskip{0pt} +%% \thispagestyle{empty} +%% \pagestyle{empty} + +% A4 modified by Eneko +\setlength{\paperwidth}{21cm} % A4 +\setlength{\paperheight}{29.7cm}% A4 +\setlength\topmargin{-0.5cm} +\setlength\oddsidemargin{0cm} +\setlength\textheight{24.7cm} +\setlength\textwidth{16.0cm} +\setlength\columnsep{0.6cm} +\newlength\titlebox +\setlength\titlebox{2.00in} +\setlength\headheight{5pt} +\setlength\headsep{0pt} +\thispagestyle{empty} +\pagestyle{empty} + + +\flushbottom \twocolumn \sloppy + +% We're never going to need a table of contents, so just flush it to +% save space --- suggested by drstrip@sandia-2 +\def\addcontentsline#1#2#3{} + +% Title stuff, taken from deproc. +\def\maketitle{\par + \begingroup + \def\thefootnote{\fnsymbol{footnote}} + \def\@makefnmark{\hbox to 0pt{$^{\@thefnmark}$\hss}} + \twocolumn[\@maketitle] \@thanks + \endgroup + \setcounter{footnote}{0} + \let\maketitle\relax \let\@maketitle\relax + \gdef\@thanks{}\gdef\@author{}\gdef\@title{}\let\thanks\relax} +\def\@maketitle{\vbox to \titlebox{\hsize\textwidth + \linewidth\hsize \vskip 0.125in minus 0.125in \centering + {\Large\bf \@title \par} \vskip 0.2in plus 1fil minus 0.1in + {\def\and{\unskip\enspace{\rm and}\enspace}% + \def\And{\end{tabular}\hss \egroup \hskip 1in plus 2fil + \hbox to 0pt\bgroup\hss \begin{tabular}[t]{c}\bf}% + \def\AND{\end{tabular}\hss\egroup \hfil\hfil\egroup + \vskip 0.25in plus 1fil minus 0.125in + \hbox to \linewidth\bgroup\large \hfil\hfil + \hbox to 0pt\bgroup\hss \begin{tabular}[t]{c}\bf} + \hbox to \linewidth\bgroup\large \hfil\hfil + \hbox to 0pt\bgroup\hss \begin{tabular}[t]{c}\bf\@author + \end{tabular}\hss\egroup + \hfil\hfil\egroup} + \vskip 0.3in plus 2fil minus 0.1in +}} + +% margins for abstract +\renewenvironment{abstract}% + {\centerline{\large\bf Abstract}% + \begin{list}{}% + {\setlength{\rightmargin}{0.6cm}% + \setlength{\leftmargin}{0.6cm}}% + \item[]\ignorespaces}% + {\unskip\end{list}} + +%\renewenvironment{abstract}{\centerline{\large\bf +% Abstract}\vspace{0.5ex}\begin{quote}}{\par\end{quote}\vskip 1ex} + + +% bibliography + +\def\thebibliography#1{\section*{References} + \global\def\@listi{\leftmargin\leftmargini + \labelwidth\leftmargini \advance\labelwidth-\labelsep + \topsep 1pt plus 2pt minus 1pt + \parsep 0.25ex plus 1pt \itemsep 0.25ex plus 1pt} + \list {[\arabic{enumi}]}{\settowidth\labelwidth{[#1]}\leftmargin\labelwidth + \advance\leftmargin\labelsep\usecounter{enumi}} + \def\newblock{\hskip .11em plus .33em minus -.07em} + \sloppy + \sfcode`\.=1000\relax} + +\def\@up#1{\raise.2ex\hbox{#1}} + +% most of cite format is from aclsub.sty by SMS + +% don't box citations, separate with ; and a space +% also, make the penalty between citations negative: a good place to break +% changed comma back to semicolon pj 2/1/90 +% \def\@citex[#1]#2{\if@filesw\immediate\write\@auxout{\string\citation{#2}}\fi +% \def\@citea{}\@cite{\@for\@citeb:=#2\do +% {\@citea\def\@citea{;\penalty\@citeseppen\ }\@ifundefined +% {b@\@citeb}{{\bf ?}\@warning +% {Citation `\@citeb' on page \thepage \space undefined}}% +% {\csname b@\@citeb\endcsname}}}{#1}} + +% don't box citations, separate with ; and a space +% Replaced for multiple citations (pj) +% don't box citations and also add space, semicolon between multiple citations +\def\@citex[#1]#2{\if@filesw\immediate\write\@auxout{\string\citation{#2}}\fi + \def\@citea{}\@cite{\@for\@citeb:=#2\do + {\@citea\def\@citea{; }\@ifundefined + {b@\@citeb}{{\bf ?}\@warning + {Citation `\@citeb' on page \thepage \space undefined}}% + {\csname b@\@citeb\endcsname}}}{#1}} + +% Allow short (name-less) citations, when used in +% conjunction with a bibliography style that creates labels like +% \citename{, } +% +\let\@internalcite\cite +\def\cite{\def\citename##1{##1, }\@internalcite} +\def\shortcite{\def\citename##1{}\@internalcite} +\def\newcite{\def\citename##1{{\frenchspacing##1} (}\@internalciteb} + +% Macros for \newcite, which leaves name in running text, and is +% otherwise like \shortcite. +\def\@citexb[#1]#2{\if@filesw\immediate\write\@auxout{\string\citation{#2}}\fi + \def\@citea{}\@newcite{\@for\@citeb:=#2\do + {\@citea\def\@citea{;\penalty\@m\ }\@ifundefined + {b@\@citeb}{{\bf ?}\@warning + {Citation `\@citeb' on page \thepage \space undefined}}% +{\csname b@\@citeb\endcsname}}}{#1}} +\def\@internalciteb{\@ifnextchar [{\@tempswatrue\@citexb}{\@tempswafalse\@citexb[]}} + +\def\@newcite#1#2{{#1\if@tempswa, #2\fi)}} + +\def\@biblabel#1{\def\citename##1{##1}[#1]\hfill} + +%%% More changes made by SMS (originals in latex.tex) +% Use parentheses instead of square brackets in the text. +\def\@cite#1#2{({#1\if@tempswa , #2\fi})} + +% Don't put a label in the bibliography at all. Just use the unlabeled format +% instead. +\def\thebibliography#1{\vskip\parskip% +\vskip\baselineskip% +\def\baselinestretch{1}% +\ifx\@currsize\normalsize\@normalsize\else\@currsize\fi% +\vskip-\parskip% +\vskip-\baselineskip% +\section*{References\@mkboth + {References}{References}}\list + {}{\setlength{\labelwidth}{0pt}\setlength{\leftmargin}{\parindent} + \setlength{\itemindent}{-\parindent}} + \def\newblock{\hskip .11em plus .33em minus -.07em} + \sloppy\clubpenalty4000\widowpenalty4000 + \sfcode`\.=1000\relax} +\let\endthebibliography=\endlist + +% Allow for a bibliography of sources of attested examples +\def\thesourcebibliography#1{\vskip\parskip% +\vskip\baselineskip% +\def\baselinestretch{1}% +\ifx\@currsize\normalsize\@normalsize\else\@currsize\fi% +\vskip-\parskip% +\vskip-\baselineskip% +\section*{Sources of Attested Examples\@mkboth + {Sources of Attested Examples}{Sources of Attested Examples}}\list + {}{\setlength{\labelwidth}{0pt}\setlength{\leftmargin}{\parindent} + \setlength{\itemindent}{-\parindent}} + \def\newblock{\hskip .11em plus .33em minus -.07em} + \sloppy\clubpenalty4000\widowpenalty4000 + \sfcode`\.=1000\relax} +\let\endthesourcebibliography=\endlist + +\def\@lbibitem[#1]#2{\item[]\if@filesw + { \def\protect##1{\string ##1\space}\immediate + \write\@auxout{\string\bibcite{#2}{#1}}\fi\ignorespaces}} + +\def\@bibitem#1{\item\if@filesw \immediate\write\@auxout + {\string\bibcite{#1}{\the\c@enumi}}\fi\ignorespaces} + +% sections with less space +\def\section{\@startsection {section}{1}{\z@}{-2.0ex plus + -0.5ex minus -.2ex}{1.5ex plus 0.3ex minus .2ex}{\large\bf\raggedright}} +\def\subsection{\@startsection{subsection}{2}{\z@}{-1.8ex plus + -0.5ex minus -.2ex}{0.8ex plus .2ex}{\normalsize\bf\raggedright}} +%% changed by KO to - values to get teh initial parindent right +\def\subsubsection{\@startsection{subsubsection}{3}{\z@}{-1.5ex plus + -0.5ex minus -.2ex}{0.5ex plus .2ex}{\normalsize\bf\raggedright}} +\def\paragraph{\@startsection{paragraph}{4}{\z@}{1.5ex plus + 0.5ex minus .2ex}{-1em}{\normalsize\bf}} +\def\subparagraph{\@startsection{subparagraph}{5}{\parindent}{1.5ex plus + 0.5ex minus .2ex}{-1em}{\normalsize\bf}} + +% Footnotes +\footnotesep 6.65pt % +\skip\footins 9pt plus 4pt minus 2pt +\def\footnoterule{\kern-3pt \hrule width 5pc \kern 2.6pt } +\setcounter{footnote}{0} + +% Lists and paragraphs +\parindent 1em +\topsep 4pt plus 1pt minus 2pt +\partopsep 1pt plus 0.5pt minus 0.5pt +\itemsep 2pt plus 1pt minus 0.5pt +\parsep 2pt plus 1pt minus 0.5pt + +\leftmargin 2em \leftmargini\leftmargin \leftmarginii 2em +\leftmarginiii 1.5em \leftmarginiv 1.0em \leftmarginv .5em \leftmarginvi .5em +\labelwidth\leftmargini\advance\labelwidth-\labelsep \labelsep 5pt + +\def\@listi{\leftmargin\leftmargini} +\def\@listii{\leftmargin\leftmarginii + \labelwidth\leftmarginii\advance\labelwidth-\labelsep + \topsep 2pt plus 1pt minus 0.5pt + \parsep 1pt plus 0.5pt minus 0.5pt + \itemsep \parsep} +\def\@listiii{\leftmargin\leftmarginiii + \labelwidth\leftmarginiii\advance\labelwidth-\labelsep + \topsep 1pt plus 0.5pt minus 0.5pt + \parsep \z@ \partopsep 0.5pt plus 0pt minus 0.5pt + \itemsep \topsep} +\def\@listiv{\leftmargin\leftmarginiv + \labelwidth\leftmarginiv\advance\labelwidth-\labelsep} +\def\@listv{\leftmargin\leftmarginv + \labelwidth\leftmarginv\advance\labelwidth-\labelsep} +\def\@listvi{\leftmargin\leftmarginvi + \labelwidth\leftmarginvi\advance\labelwidth-\labelsep} + +\abovedisplayskip 7pt plus2pt minus5pt% +\belowdisplayskip \abovedisplayskip +\abovedisplayshortskip 0pt plus3pt% +\belowdisplayshortskip 4pt plus3pt minus3pt% + +% Less leading in most fonts (due to the narrow columns) +% The choices were between 1-pt and 1.5-pt leading +\def\@normalsize{\@setsize\normalsize{11pt}\xpt\@xpt} +\def\small{\@setsize\small{10pt}\ixpt\@ixpt} +\def\footnotesize{\@setsize\footnotesize{10pt}\ixpt\@ixpt} +\def\scriptsize{\@setsize\scriptsize{8pt}\viipt\@viipt} 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a/papers/2010_acl_systems_sspace/figures/sspace_threading.dat b/papers/2010_acl_systems_sspace/figures/sspace_threading.dat new file mode 100644 index 00000000..5490bf6d --- /dev/null +++ b/papers/2010_acl_systems_sspace/figures/sspace_threading.dat @@ -0,0 +1,8 @@ +0 RRI BEAGLE COALS LSA HAL RI VSM +2 168.381139 196.830427 129.175135 162.067348 105.573463 183.253403 175.283352 +3 206.950989 308.547121 175.163755 215.463275 98.615975 241.789615 209.481794 +4 240.895988 402.740478 189.118626 220.889798 93.869126 284.394524 222.740486 +5 262.617842 494.575479 210.906439 215.678442 99.256886 294.694025 203.562372 +6 255.752965 553.824797 230.219942 197.440293 95.279001 299.672373 198.598021 +7 266.278710 634.281798 240.965799 193.873429 101.829383 301.050141 192.255931 +8 258.078490 706.991807 261.885415 189.576476 110.724939 298.437946 182.100032 diff --git a/papers/2010_acl_systems_sspace/figures/sspace_threading.in b/papers/2010_acl_systems_sspace/figures/sspace_threading.in new file mode 100644 index 00000000..a4a41392 --- /dev/null +++ b/papers/2010_acl_systems_sspace/figures/sspace_threading.in @@ -0,0 +1,27 @@ +set terminal postscript enhanced color 20 +set output 'threading.eps' +set bar 1.000000 +set style rectangle back fc lt -3 fillstyle solid 1.00 border -1 +set key inside left top vertical Left noreverse enhanced autotitles columnhead nobo +set datafile missing '-' +#set data style linespoints +set style data linespoints# linewidth 5 +set xtics border in scale 1,0.5 nomirror offset character 0, 0, 0 +set rrange [ * : * ] noreverse nowriteback # (currently [0.00000:10.0000] ) +set trange [ * : * ] noreverse nowriteback # (currently [-5.00000:5.00000] ) +set urange [ * : * ] noreverse nowriteback # (currently [-5.00000:5.00000] ) +set vrange [ * : * ] noreverse nowriteback # (currently [-5.00000:5.00000] ) +set ylabel offset character 0, 0, 0 font "" textcolor lt -1 rotate by 90 +set ylabel "Percentage improvement" font "Times-Roman,30" +set xlabel "Number of threads" font "Times-Roman,30" +set y2label offset character 0, 0, 0 font "" textcolor lt -1 +set cblabel offset character 0, 0, 0 font "" textcolor lt -1 +set locale "C" +set pointsize 2 +plot 'sspace_threading.dat' using 2:xtic(1) lw 2 pt 14 lc 'black', \ +'' u 3 lw 2 lt 1 lc rgb 'dark-turquoise' pt 8, \ +'' u 4 lw 2 lt 1 lc rgb 'dark-violet' pt 6, \ +'' u 5 lw 2 lt 1 lc rgb 'red' pt 2, \ +'' u 6 lw 2 lt 1 lc rgb 'dark-green' pt 10, \ +'' u 7 lw 2 lt 1 lc rgb 'dark-goldenrod' pt 4, \ +'' u 8 lw 2 lt 1 lc rgb 'blue' pt 12 diff --git a/papers/2010_acl_systems_sspace/figures/sspace_timing-as-tokens.dat b/papers/2010_acl_systems_sspace/figures/sspace_timing-as-tokens.dat new file mode 100644 index 00000000..1caefd17 --- /dev/null +++ b/papers/2010_acl_systems_sspace/figures/sspace_timing-as-tokens.dat @@ -0,0 +1,8 @@ +# 0 RandomIndexing +1 1 +63548235 648.386 +125017543 1226.765 +172627750 1629.307 +227618615 2071.549 +267218636 2396.782 +295872332 2607.288 diff --git a/papers/2010_acl_systems_sspace/figures/sspace_timing-as-tokens2.dat b/papers/2010_acl_systems_sspace/figures/sspace_timing-as-tokens2.dat new file mode 100644 index 00000000..85de9093 --- /dev/null +++ b/papers/2010_acl_systems_sspace/figures/sspace_timing-as-tokens2.dat @@ -0,0 +1,5 @@ +# 0 RandomIndexing +1 1 +63548235 -1 +125017543 -31226.765 +295872332 -13 diff --git a/papers/2010_acl_systems_sspace/figures/sspace_timing.dat b/papers/2010_acl_systems_sspace/figures/sspace_timing.dat new file mode 100644 index 00000000..94fc0877 --- /dev/null +++ b/papers/2010_acl_systems_sspace/figures/sspace_timing.dat @@ -0,0 +1,10 @@ +0 Coals Lsa Isa Beagle Hal RandomIndexing +5000 431.654 57.663 69.789 120.269 25.826 12.458 +10000 550.561 114.019 136.135 237.363 46.537 21.449 +15000 715.208 142.420 196.842 352.207 70.732 30.159 +20000 776.064 178.792 258.587 481.069 80.808 46.354 +25000 822.111 215.958 327.871 605.206 129.635 55.742 +30000 955.049 252.129 389.921 698.043 145.182 54.354 +35000 1041.241 293.916 444.058 828.086 146.954 62.028 +40000 1133.565 343.412 522.012 945.325 162.192 84.337 +45000 1189.925 377.201 575.307 1047.871 187.806 76.310 diff --git a/papers/2010_acl_systems_sspace/figures/sspace_timing.in b/papers/2010_acl_systems_sspace/figures/sspace_timing.in new file mode 100644 index 00000000..28c51542 --- /dev/null +++ b/papers/2010_acl_systems_sspace/figures/sspace_timing.in @@ -0,0 +1,48 @@ +#set term x11 +set terminal postscript enhanced color 20 +set output 'timing.eps' +set bar 1.000000 +set style rectangle back fc lt -3 fillstyle solid 1.00 border -1 +set key inside left top vertical Left noreverse enhanced autotitles columnhead nobo +set datafile missing '-' +#set data style linespoints +#set xtics border in scale 1,0.5 nomirror rotate by -45 offset character 0, 0, 0 +set ylabel offset character 0, 0, 0 font "" textcolor lt -1 rotate by 90 +set ylabel "Seconds" font "Times-Roman,30" +set xlabel "Number of documents" font "Times-Roman,30" +#set y2label offset character 0, 0, 0 font "" textcolor lt -1 rotate by 90 +#set cblabel offset character 0, 0, 0 font "" textcolor lt -1 rotate by 90 +set xtics (100000,200000,300000,400000,500000,600000,700000) nomirror + +#set x2tics (63548235,125017543,172627750,227618615,267218636,295872332) +#set x2tics (63500000,125000000,173000000,228000000,267000000,296000000.0) + +#46464819 +#49312055 +#38729682 +#set x2tics ("63548235" 63548235, "125017543" 63548235+46464819, "172627750" 63548235+46464819*2, "227618615" 63548235+46464819*3, "267218636" 63548235+46464819*4, "29587233" 63548235+46464819*5 +set x2tics ("63.5M" 63548235, "125M" 63548235+46464819, "173M" 63548235+46464819*2, "228M" 63548235+46464819*3, "267M" 63548235+46464819*4, "296M" 63548235+46464819*5) +#set x2tics ("63500000" 055, "125000000" 49312055*2, "173000000" 49312055*3, "228000000" 49312055*4, "267000000" 49312055*5, "296000000" 49312055*6) + +set ytics (0,5000,10000,15000,20000,25000) nomirror +set x2label "Tokens in Documents (in millions)" font "Times-Roman,30" +set locale "C" +#set autoscale x2 +#set autoscale x +#set xrange [100000 : 600001] +#set x2range [63548235 : 295872332] +set yrange[0:30000] +#set log y +#set grid +set style line 8 lw 3 +#plot 'sspace_timing2.dat' using 2:xtic(1) lw 3 , '' u 3 lw 3, '' u 4 lw 3, '' u 5 lw 3, '' u 6 lw 3, '' u 7 ls 8, 'sspace_timing-as-tokens2.dat' using 1:2 title '' axis x2y1 lw 3 + +set pointsize 2 +plot 'sspace_timing2.dat' u 1:2 with linespoints lw 2 pt 2 title 'LSA', \ + '' u 1:3 with linespoints lw 2 pt 12 lt 1 lc rgb 'blue' title 'VSM', \ + '' u 1:4 with linespoints lw 2 pt 6 lt 1 lc rgb 'dark-violet' title 'COALS', \ + '' u 1:5 with linespoints lw 2 pt 8 lt 1 lc rgb 'dark-turquoise' title 'BEAGLE', \ + '' u 1:6 with linespoints lw 2 pt 10 lt 1 lc rgb 'dark-green' title 'HAL', \ + '' u 1:7 with linespoints lw 2 pt 4 lt 1 lc rgb 'dark-goldenrod' title 'RI', \ + 'sspace_timing-as-tokens2.dat' using 1:2 title '' axis x2y1 lw 3 +# plot 'sspace_timing2.dat' u 1:2 lw 3 title 'LSA' pt 4, '' u 1:3 lw 3 title 'VSM', '' u 1:4 lw 3 title 'COALS', '' u 1:5 lw 3 title 'BEAGLE', '' u 1:6 lw 3 title 'HAL', '' u 1:7 ls 8 title 'RI', 'sspace_timing-as-tokens2.dat' using 1:2 title '' axis x2y1 lw 3 diff --git a/papers/2010_acl_systems_sspace/figures/sspace_timing2.dat b/papers/2010_acl_systems_sspace/figures/sspace_timing2.dat new file mode 100644 index 00000000..9965e064 --- /dev/null +++ b/papers/2010_acl_systems_sspace/figures/sspace_timing2.dat @@ -0,0 +1,8 @@ +0 LSA Vsm Coals Beagle HAL RandomIndexing +100000 642.762 1083.758 1167.676 3781.046 67.254 648.386 +200000 988.316 4415.011 1767.351 7669.628 163.025 1226.765 +300000 1335.410 9602.195 2598.485 10125.346 213.633 1629.307 +350000 1543.524 - 5777.288 - - - +400000 1741.694 18486.065 - 13970.586 278.585 2071.549 +500000 2082.895 27475.880 - 15784.694 318.052 2396.782 +600000 2330.569 - - 17407.680 376.782 2607.288 diff --git 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-0,0 +1,1322 @@ + +% BibTeX `acl' style file for BibTeX version 0.99c, LaTeX version 2.09 +% This version was made by modifying `aaai-named' format based on the master +% file by Oren Patashnik (PATASHNIK@SCORE.STANFORD.EDU) + +% Copyright (C) 1985, all rights reserved. +% Modifications Copyright 1988, Peter F. Patel-Schneider +% Further modifictions by Stuart Shieber, 1991, and Fernando Pereira, 1992. +% Copying of this file is authorized only if either +% (1) you make absolutely no changes to your copy, including name, or +% (2) if you do make changes, you name it something other than +% btxbst.doc, plain.bst, unsrt.bst, alpha.bst, and abbrv.bst. +% This restriction helps ensure that all standard styles are identical. + +% There are undoubtably bugs in this style. If you make bug fixes, +% improvements, etc. please let me know. My e-mail address is: +% pfps@spar.slb.com + +% Citation format: [author-last-name, year] +% [author-last-name and author-last-name, year] +% [author-last-name {\em et al.}, year] +% +% Reference list ordering: alphabetical by author or whatever passes +% for author in the absence of one. +% +% This BibTeX style has support for short (year only) citations. This +% is done by having the citations actually look like +% \citename{name-info, }year +% The LaTeX style has to have the following +% \let\@internalcite\cite +% \def\cite{\def\citename##1{##1}\@internalcite} +% \def\shortcite{\def\citename##1{}\@internalcite} +% \def\@biblabel#1{\def\citename##1{##1}[#1]\hfill} +% which makes \shortcite the macro for short citations. + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% Changes made by SMS for thesis style +% no emphasis on "et al." +% "Ph.D." includes periods (not "PhD") +% moved year to immediately after author's name +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +ENTRY + { address + author + booktitle + chapter + edition + editor + howpublished + institution + journal + key + month + note + number + organization + pages + publisher + school + series + title + type + volume + year + } + {} + { label extra.label sort.label } + +INTEGERS { output.state before.all mid.sentence after.sentence after.block } + +FUNCTION {init.state.consts} +{ #0 'before.all := + #1 'mid.sentence := + #2 'after.sentence := + #3 'after.block := +} + +STRINGS { s t } + +FUNCTION {output.nonnull} +{ 's := + output.state mid.sentence = + { ", " * write$ } + { output.state after.block = + { add.period$ write$ + newline$ + "\newblock " write$ + } + { output.state before.all = + 'write$ + { add.period$ " " * write$ } + if$ + } + if$ + mid.sentence 'output.state := + } + if$ + s +} + +FUNCTION {output} +{ duplicate$ empty$ + 'pop$ + 'output.nonnull + if$ +} + +FUNCTION {output.check} +{ 't := + duplicate$ empty$ + { pop$ "empty " t * " in " * cite$ * warning$ } + 'output.nonnull + if$ +} + +FUNCTION {output.bibitem} +{ newline$ + + "\bibitem[" write$ + label write$ + "]{" write$ + + cite$ write$ + "}" write$ + newline$ + "" + before.all 'output.state := +} + +FUNCTION {fin.entry} +{ add.period$ + write$ + newline$ +} + +FUNCTION {new.block} +{ output.state before.all = + 'skip$ + { after.block 'output.state := } + if$ +} + +FUNCTION {new.sentence} +{ output.state after.block = + 'skip$ + { output.state before.all = + 'skip$ + { after.sentence 'output.state := } + if$ + } + if$ +} + +FUNCTION {not} +{ { #0 } + { #1 } + if$ +} + +FUNCTION {and} +{ 'skip$ + { pop$ #0 } + if$ +} + +FUNCTION {or} +{ { pop$ #1 } + 'skip$ + if$ +} + +FUNCTION {new.block.checka} +{ empty$ + 'skip$ + 'new.block + if$ +} + +FUNCTION {new.block.checkb} +{ empty$ + swap$ empty$ + and + 'skip$ + 'new.block + if$ +} + +FUNCTION {new.sentence.checka} +{ empty$ + 'skip$ + 'new.sentence + if$ +} + +FUNCTION {new.sentence.checkb} +{ empty$ + swap$ empty$ + and + 'skip$ + 'new.sentence + if$ +} + +FUNCTION {field.or.null} +{ duplicate$ empty$ + { pop$ "" } + 'skip$ + if$ +} + +FUNCTION {emphasize} +{ duplicate$ empty$ + { pop$ "" } + { "{\em " swap$ * "}" * } + if$ +} + +INTEGERS { nameptr namesleft numnames } + +FUNCTION {format.names} +{ 's := + #1 'nameptr := + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + + { s nameptr "{ff~}{vv~}{ll}{, jj}" format.name$ 't := + + nameptr #1 > + { namesleft #1 > + { ", " * t * } + { numnames #2 > + { "," * } + 'skip$ + if$ + t "others" = + { " et~al." * } + { " and " * t * } + if$ + } + if$ + } + 't + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {format.authors} +{ author empty$ + { "" } + { author format.names } + if$ +} + +FUNCTION {format.editors} +{ editor empty$ + { "" } + { editor format.names + editor num.names$ #1 > + { ", editors" * } + { ", editor" * } + if$ + } + if$ +} + +FUNCTION {format.title} +{ title empty$ + { "" } + + { title "t" change.case$ } + + if$ +} + +FUNCTION {n.dashify} +{ 't := + "" + { t empty$ not } + { t #1 #1 substring$ "-" = + { t #1 #2 substring$ "--" = not + { "--" * + t #2 global.max$ substring$ 't := + } + { { t #1 #1 substring$ "-" = } + { "-" * + t #2 global.max$ substring$ 't := + } + while$ + } + if$ + } + { t #1 #1 substring$ * + t #2 global.max$ substring$ 't := + } + if$ + } + while$ +} + +FUNCTION {format.date} +{ year empty$ + { month empty$ + { "" } + { "there's a month but no year in " cite$ * warning$ + month + } + if$ + } + { month empty$ + { "" } + { month } + if$ + } + if$ +} + +FUNCTION {format.btitle} +{ title emphasize +} + +FUNCTION {tie.or.space.connect} +{ duplicate$ text.length$ #3 < + { "~" } + { " " } + if$ + swap$ * * +} + +FUNCTION {either.or.check} +{ empty$ + 'pop$ + { "can't use both " swap$ * " fields in " * cite$ * warning$ } + if$ +} + +FUNCTION {format.bvolume} +{ volume empty$ + { "" } + { "volume" volume tie.or.space.connect + series empty$ + 'skip$ + { " of " * series emphasize * } + if$ + "volume and number" number either.or.check + } + if$ +} + +FUNCTION {format.number.series} +{ volume empty$ + { number empty$ + { series field.or.null } + { output.state mid.sentence = + { "number" } + { "Number" } + if$ + number tie.or.space.connect + series empty$ + { "there's a number but no series in " cite$ * warning$ } + { " in " * series * } + if$ + } + if$ + } + { "" } + if$ +} + +FUNCTION {format.edition} +{ edition empty$ + { "" } + { output.state mid.sentence = + { edition "l" change.case$ " edition" * } + { edition "t" change.case$ " edition" * } + if$ + } + if$ +} + +INTEGERS { multiresult } + +FUNCTION {multi.page.check} +{ 't := + #0 'multiresult := + { multiresult not + t empty$ not + and + } + { t #1 #1 substring$ + duplicate$ "-" = + swap$ duplicate$ "," = + swap$ "+" = + or or + { #1 'multiresult := } + { t #2 global.max$ substring$ 't := } + if$ + } + while$ + multiresult +} + +FUNCTION {format.pages} +{ pages empty$ + { "" } + { pages multi.page.check + { "pages" pages n.dashify tie.or.space.connect } + { "page" pages tie.or.space.connect } + if$ + } + if$ +} + +FUNCTION {format.year.label} +{ year extra.label * +} + +FUNCTION {format.vol.num.pages} +{ volume field.or.null + number empty$ + 'skip$ + { "(" number * ")" * * + volume empty$ + { "there's a number but no volume in " cite$ * warning$ } + 'skip$ + if$ + } + if$ + pages empty$ + 'skip$ + { duplicate$ empty$ + { pop$ format.pages } + { ":" * pages n.dashify * } + if$ + } + if$ +} + +FUNCTION {format.chapter.pages} +{ chapter empty$ + 'format.pages + { type empty$ + { "chapter" } + { type "l" change.case$ } + if$ + chapter tie.or.space.connect + pages empty$ + 'skip$ + { ", " * format.pages * } + if$ + } + if$ +} + +FUNCTION {format.in.ed.booktitle} +{ booktitle empty$ + { "" } + { editor empty$ + { "In " booktitle emphasize * } + { "In " format.editors * ", " * booktitle emphasize * } + if$ + } + if$ +} + +FUNCTION {empty.misc.check} +{ author empty$ title empty$ howpublished empty$ + month empty$ year empty$ note empty$ + and and and and and + + key empty$ not and + + { "all relevant fields are empty in " cite$ * warning$ } + 'skip$ + if$ +} + +FUNCTION {format.thesis.type} +{ type empty$ + 'skip$ + { pop$ + type "t" change.case$ + } + if$ +} + +FUNCTION {format.tr.number} +{ type empty$ + { "Technical Report" } + 'type + if$ + number empty$ + { "t" change.case$ } + { number tie.or.space.connect } + if$ +} + +FUNCTION {format.article.crossref} +{ key empty$ + { journal empty$ + { "need key or journal for " cite$ * " to crossref " * crossref * + warning$ + "" + } + { "In {\em " journal * "\/}" * } + if$ + } + { "In " key * } + if$ + " \cite{" * crossref * "}" * +} + +FUNCTION {format.crossref.editor} +{ editor #1 "{vv~}{ll}" format.name$ + editor num.names$ duplicate$ + #2 > + { pop$ " et~al." * } + { #2 < + 'skip$ + { editor #2 "{ff }{vv }{ll}{ jj}" format.name$ "others" = + { " et~al." * } + { " and " * editor #2 "{vv~}{ll}" format.name$ * } + if$ + } + if$ + } + if$ +} + +FUNCTION {format.book.crossref} +{ volume empty$ + { "empty volume in " cite$ * "'s crossref of " * crossref * warning$ + "In " + } + { "Volume" volume tie.or.space.connect + " of " * + } + if$ + editor empty$ + editor field.or.null author field.or.null = + or + { key empty$ + { series empty$ + { "need editor, key, or series for " cite$ * " to crossref " * + crossref * warning$ + "" * + } + { "{\em " * series * "\/}" * } + if$ + } + { key * } + if$ + } + { format.crossref.editor * } + if$ + " \cite{" * crossref * "}" * +} + +FUNCTION {format.incoll.inproc.crossref} +{ editor empty$ + editor field.or.null author field.or.null = + or + { key empty$ + { booktitle empty$ + { "need editor, key, or booktitle for " cite$ * " to crossref " * + crossref * warning$ + "" + } + { "In {\em " booktitle * "\/}" * } + if$ + } + { "In " key * } + if$ + } + { "In " format.crossref.editor * } + if$ + " \cite{" * crossref * "}" * +} + +FUNCTION {article} +{ output.bibitem + format.authors "author" output.check + new.block + format.year.label "year" output.check + new.block + format.title "title" output.check + new.block + crossref missing$ + { journal emphasize "journal" output.check + format.vol.num.pages output + format.date output + } + { format.article.crossref output.nonnull + format.pages output + } + if$ + new.block + note output + fin.entry +} + +FUNCTION {book} +{ output.bibitem + author empty$ + { format.editors "author and editor" output.check } + { format.authors output.nonnull + crossref missing$ + { "author and editor" editor either.or.check } + 'skip$ + if$ + } + if$ + new.block + format.year.label "year" output.check + new.block + format.btitle "title" output.check + crossref missing$ + { format.bvolume output + new.block + format.number.series output + new.sentence + publisher "publisher" output.check + address output + } + { new.block + format.book.crossref output.nonnull + } + if$ + format.edition output + format.date output + new.block + note output + fin.entry +} + +FUNCTION {booklet} +{ output.bibitem + format.authors output + new.block + format.year.label "year" output.check + new.block + format.title "title" output.check + howpublished address new.block.checkb + howpublished output + address output + format.date output + new.block + note output + fin.entry +} + +FUNCTION {inbook} +{ output.bibitem + author empty$ + { format.editors "author and editor" output.check } + { format.authors output.nonnull + crossref missing$ + { "author and editor" editor either.or.check } + 'skip$ + if$ + } + if$ + format.year.label "year" output.check + new.block + new.block + format.btitle "title" output.check + crossref missing$ + { format.bvolume output + format.chapter.pages "chapter and pages" output.check + new.block + format.number.series output + new.sentence + publisher "publisher" output.check + address output + } + { format.chapter.pages "chapter and pages" output.check + new.block + format.book.crossref output.nonnull + } + if$ + format.edition output + format.date output + new.block + note output + fin.entry +} + +FUNCTION {incollection} +{ output.bibitem + format.authors "author" output.check + new.block + format.year.label "year" output.check + new.block + format.title "title" output.check + new.block + crossref missing$ + { format.in.ed.booktitle "booktitle" output.check + format.bvolume output + format.number.series output + format.chapter.pages output + new.sentence + publisher "publisher" output.check + address output + format.edition output + format.date output + } + { format.incoll.inproc.crossref output.nonnull + format.chapter.pages output + } + if$ + new.block + note output + fin.entry +} + +FUNCTION {inproceedings} +{ output.bibitem + format.authors "author" output.check + new.block + format.year.label "year" output.check + new.block + format.title "title" output.check + new.block + crossref missing$ + { format.in.ed.booktitle "booktitle" output.check + format.bvolume output + format.number.series output + format.pages output + address empty$ + { organization publisher new.sentence.checkb + organization output + publisher output + format.date output + } + { address output.nonnull + format.date output + new.sentence + organization output + publisher output + } + if$ + } + { format.incoll.inproc.crossref output.nonnull + format.pages output + } + if$ + new.block + note output + fin.entry +} + +FUNCTION {conference} { inproceedings } + +FUNCTION {manual} +{ output.bibitem + author empty$ + { organization empty$ + 'skip$ + { organization output.nonnull + address output + } + if$ + } + { format.authors output.nonnull } + if$ + format.year.label "year" output.check + new.block + new.block + format.btitle "title" output.check + author empty$ + { organization empty$ + { address new.block.checka + address output + } + 'skip$ + if$ + } + { organization address new.block.checkb + organization output + address output + } + if$ + format.edition output + format.date output + new.block + note output + fin.entry +} + +FUNCTION {mastersthesis} +{ output.bibitem + format.authors "author" output.check + new.block + format.year.label "year" output.check + new.block + format.title "title" output.check + new.block + "Master's thesis" format.thesis.type output.nonnull + school "school" output.check + address output + format.date output + new.block + note output + fin.entry +} + +FUNCTION {misc} +{ output.bibitem + format.authors output + new.block + format.year.label output + new.block + title howpublished new.block.checkb + format.title output + howpublished new.block.checka + howpublished output + format.date output + new.block + note output + fin.entry + empty.misc.check +} + +FUNCTION {phdthesis} +{ output.bibitem + format.authors "author" output.check + new.block + format.year.label "year" output.check + new.block + format.btitle "title" output.check + new.block + "{Ph.D.} thesis" format.thesis.type output.nonnull + school "school" output.check + address output + format.date output + new.block + note output + fin.entry +} + +FUNCTION {proceedings} +{ output.bibitem + editor empty$ + { organization output } + { format.editors output.nonnull } + if$ + new.block + format.year.label "year" output.check + new.block + format.btitle "title" output.check + format.bvolume output + format.number.series output + address empty$ + { editor empty$ + { publisher new.sentence.checka } + { organization publisher new.sentence.checkb + organization output + } + if$ + publisher output + format.date output + } + { address output.nonnull + format.date output + new.sentence + editor empty$ + 'skip$ + { organization output } + if$ + publisher output + } + if$ + new.block + note output + fin.entry +} + +FUNCTION {techreport} +{ output.bibitem + format.authors "author" output.check + new.block + format.year.label "year" output.check + new.block + format.title "title" output.check + new.block + format.tr.number output.nonnull + institution "institution" output.check + address output + format.date output + new.block + note output + fin.entry +} + +FUNCTION {unpublished} +{ output.bibitem + format.authors "author" output.check + new.block + format.year.label "year" output.check + new.block + format.title "title" output.check + new.block + note "note" output.check + format.date output + fin.entry +} + +FUNCTION {default.type} { misc } + +MACRO {jan} {"January"} + +MACRO {feb} {"February"} + +MACRO {mar} {"March"} + +MACRO {apr} {"April"} + +MACRO {may} {"May"} + +MACRO {jun} {"June"} + +MACRO {jul} {"July"} + +MACRO {aug} {"August"} + +MACRO {sep} {"September"} + +MACRO {oct} {"October"} + +MACRO {nov} {"November"} + +MACRO {dec} {"December"} + +MACRO {acmcs} {"ACM Computing Surveys"} + +MACRO {acta} {"Acta Informatica"} + +MACRO {cacm} {"Communications of the ACM"} + +MACRO {ibmjrd} {"IBM Journal of Research and Development"} + +MACRO {ibmsj} {"IBM Systems Journal"} + +MACRO {ieeese} {"IEEE Transactions on Software Engineering"} + +MACRO {ieeetc} {"IEEE Transactions on Computers"} + +MACRO {ieeetcad} + {"IEEE Transactions on Computer-Aided Design of Integrated Circuits"} + +MACRO {ipl} {"Information Processing Letters"} + +MACRO {jacm} {"Journal of the ACM"} + +MACRO {jcss} {"Journal of Computer and System Sciences"} + +MACRO {scp} {"Science of Computer Programming"} + +MACRO {sicomp} {"SIAM Journal on Computing"} + +MACRO {tocs} {"ACM Transactions on Computer Systems"} + +MACRO {tods} {"ACM Transactions on Database Systems"} + +MACRO {tog} {"ACM Transactions on Graphics"} + +MACRO {toms} {"ACM Transactions on Mathematical Software"} + +MACRO {toois} {"ACM Transactions on Office Information Systems"} + +MACRO {toplas} {"ACM Transactions on Programming Languages and Systems"} + +MACRO {tcs} {"Theoretical Computer Science"} + +READ + +FUNCTION {sortify} +{ purify$ + "l" change.case$ +} + +INTEGERS { len } + +FUNCTION {chop.word} +{ 's := + 'len := + s #1 len substring$ = + { s len #1 + global.max$ substring$ } + 's + if$ +} + +INTEGERS { et.al.char.used } + +FUNCTION {initialize.et.al.char.used} +{ #0 'et.al.char.used := +} + +EXECUTE {initialize.et.al.char.used} + +FUNCTION {format.lab.names} +{ 's := + s num.names$ 'numnames := + + numnames #1 = + { s #1 "{vv }{ll}" format.name$ } + { numnames #2 = + { s #1 "{vv }{ll }and " format.name$ s #2 "{vv }{ll}" format.name$ * + } + { s #1 "{vv }{ll }\bgroup et al.\egroup " format.name$ } + if$ + } + if$ + +} + +FUNCTION {author.key.label} +{ author empty$ + { key empty$ + + { cite$ #1 #3 substring$ } + + { key #3 text.prefix$ } + if$ + } + { author format.lab.names } + if$ +} + +FUNCTION {author.editor.key.label} +{ author empty$ + { editor empty$ + { key empty$ + + { cite$ #1 #3 substring$ } + + { key #3 text.prefix$ } + if$ + } + { editor format.lab.names } + if$ + } + { author format.lab.names } + if$ +} + +FUNCTION {author.key.organization.label} +{ author empty$ + { key empty$ + { organization empty$ + + { cite$ #1 #3 substring$ } + + { "The " #4 organization chop.word #3 text.prefix$ } + if$ + } + { key #3 text.prefix$ } + if$ + } + { author format.lab.names } + if$ +} + +FUNCTION {editor.key.organization.label} +{ editor empty$ + { key empty$ + { organization empty$ + + { cite$ #1 #3 substring$ } + + { "The " #4 organization chop.word #3 text.prefix$ } + if$ + } + { key #3 text.prefix$ } + if$ + } + { editor format.lab.names } + if$ +} + +FUNCTION {calc.label} +{ type$ "book" = + type$ "inbook" = + or + 'author.editor.key.label + { type$ "proceedings" = + 'editor.key.organization.label + { type$ "manual" = + 'author.key.organization.label + 'author.key.label + if$ + } + if$ + } + if$ + duplicate$ + + "\protect\citename{" swap$ * "}" * + year field.or.null purify$ * + 'label := + year field.or.null purify$ * + + sortify 'sort.label := +} + +FUNCTION {sort.format.names} +{ 's := + #1 'nameptr := + "" + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + { nameptr #1 > + { " " * } + 'skip$ + if$ + + s nameptr "{vv{ } }{ll{ }}{ ff{ }}{ jj{ }}" format.name$ 't := + + nameptr numnames = t "others" = and + { "et al" * } + { t sortify * } + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {sort.format.title} +{ 't := + "A " #2 + "An " #3 + "The " #4 t chop.word + chop.word + chop.word + sortify + #1 global.max$ substring$ +} + +FUNCTION {author.sort} +{ author empty$ + { key empty$ + { "to sort, need author or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { author sort.format.names } + if$ +} + +FUNCTION {author.editor.sort} +{ author empty$ + { editor empty$ + { key empty$ + { "to sort, need author, editor, or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { editor sort.format.names } + if$ + } + { author sort.format.names } + if$ +} + +FUNCTION {author.organization.sort} +{ author empty$ + { organization empty$ + { key empty$ + { "to sort, need author, organization, or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { "The " #4 organization chop.word sortify } + if$ + } + { author sort.format.names } + if$ +} + +FUNCTION {editor.organization.sort} +{ editor empty$ + { organization empty$ + { key empty$ + { "to sort, need editor, organization, or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { "The " #4 organization chop.word sortify } + if$ + } + { editor sort.format.names } + if$ +} + +FUNCTION {presort} + +{ calc.label + sort.label + " " + * + type$ "book" = + + type$ "inbook" = + or + 'author.editor.sort + { type$ "proceedings" = + 'editor.organization.sort + { type$ "manual" = + 'author.organization.sort + 'author.sort + if$ + } + if$ + } + if$ + + * + + " " + * + year field.or.null sortify + * + " " + * + title field.or.null + sort.format.title + * + #1 entry.max$ substring$ + 'sort.key$ := +} + +ITERATE {presort} + +SORT + +STRINGS { longest.label last.sort.label next.extra } + +INTEGERS { longest.label.width last.extra.num } + +FUNCTION {initialize.longest.label} +{ "" 'longest.label := + #0 int.to.chr$ 'last.sort.label := + "" 'next.extra := + #0 'longest.label.width := + #0 'last.extra.num := +} + +FUNCTION {forward.pass} +{ last.sort.label sort.label = + { last.extra.num #1 + 'last.extra.num := + last.extra.num int.to.chr$ 'extra.label := + } + { "a" chr.to.int$ 'last.extra.num := + "" 'extra.label := + sort.label 'last.sort.label := + } + if$ +} + +FUNCTION {reverse.pass} +{ next.extra "b" = + { "a" 'extra.label := } + 'skip$ + if$ + label extra.label * 'label := + label width$ longest.label.width > + { label 'longest.label := + label width$ 'longest.label.width := + } + 'skip$ + if$ + extra.label 'next.extra := +} + +EXECUTE {initialize.longest.label} + +ITERATE {forward.pass} + +REVERSE {reverse.pass} + +FUNCTION {begin.bib} + +{ et.al.char.used + { "\newcommand{\etalchar}[1]{$^{#1}$}" write$ newline$ } + 'skip$ + if$ + preamble$ empty$ + + 'skip$ + { preamble$ write$ newline$ } + if$ + + "\begin{thebibliography}{" "}" * write$ newline$ + +} + +EXECUTE {begin.bib} + +EXECUTE {init.state.consts} + +ITERATE {call.type$} + +FUNCTION {end.bib} +{ newline$ + "\end{thebibliography}" write$ newline$ +} + +EXECUTE {end.bib} + diff --git a/papers/2010_gems_lpsa/acl2010.pdf b/papers/2010_gems_lpsa/acl2010.pdf new file mode 100644 index 00000000..4966a7e7 Binary files /dev/null and b/papers/2010_gems_lpsa/acl2010.pdf differ diff --git a/papers/2010_gems_lpsa/acl2010.sty b/papers/2010_gems_lpsa/acl2010.sty new file mode 100644 index 00000000..e580ae8e --- /dev/null +++ b/papers/2010_gems_lpsa/acl2010.sty @@ -0,0 +1,370 @@ +% File acl2010.sty +% same as -- +% File acl-ijcnlp2009.sty +% same as -- +% File eacl2006.sty +% September 19, 2005 +% Contact: e.agirre@ehu.es or Sergi.Balari@uab.es + +% This is the LaTeX style file for EACL 2006. It is nearly identical to the +% style files for ACL2005, ACL 2002, ACL 2001, ACL 2000, EACL 95 and EACL +% 99. +% +% Changes made include: adapt layout to A4 and centimeters, widden abstract + +% This is the LaTeX style file for ACL 2000. It is nearly identical to the +% style files for EACL 95 and EACL 99. Minor changes include editing the +% instructions to reflect use of \documentclass rather than \documentstyle +% and removing the white space before the title on the first page +% -- John Chen, June 29, 2000 + +% To convert from submissions prepared using the style file aclsub.sty +% prepared for the ACL 2000 conference, proceed as follows: +% 1) Remove submission-specific information: \whichsession, \id, +% \wordcount, \otherconferences, \area, \keywords +% 2) \summary should be removed. The summary material should come +% after \maketitle and should be in the ``abstract'' environment +% 3) Check all citations. This style should handle citations correctly +% and also allows multiple citations separated by semicolons. +% 4) Check figures and examples. Because the final format is double- +% column, some adjustments may have to be made to fit text in the column +% or to choose full-width (\figure*} figures. +% 5) Change the style reference from aclsub to acl2000, and be sure +% this style file is in your TeX search path + + +% This is the LaTeX style file for EACL-95. It is identical to the +% style file for ANLP '94 except that the margins are adjusted for A4 +% paper. -- abney 13 Dec 94 + +% The ANLP '94 style file is a slightly modified +% version of the style used for AAAI and IJCAI, using some changes +% prepared by Fernando Pereira and others and some minor changes +% by Paul Jacobs. + +% Papers prepared using the aclsub.sty file and acl.bst bibtex style +% should be easily converted to final format using this style. +% (1) Submission information (\wordcount, \subject, and \makeidpage) +% should be removed. +% (2) \summary should be removed. The summary material should come +% after \maketitle and should be in the ``abstract'' environment +% (between \begin{abstract} and \end{abstract}). +% (3) Check all citations. This style should handle citations correctly +% and also allows multiple citations separated by semicolons. +% (4) Check figures and examples. Because the final format is double- +% column, some adjustments may have to be made to fit text in the column +% or to choose full-width (\figure*} figures. + +% Place this in a file called aclap.sty in the TeX search path. +% (Placing it in the same directory as the paper should also work.) + +% Prepared by Peter F. Patel-Schneider, liberally using the ideas of +% other style hackers, including Barbara Beeton. +% This style is NOT guaranteed to work. It is provided in the hope +% that it will make the preparation of papers easier. +% +% There are undoubtably bugs in this style. If you make bug fixes, +% improvements, etc. please let me know. My e-mail address is: +% pfps@research.att.com + +% Papers are to be prepared using the ``acl'' bibliography style, +% as follows: +% \documentclass[11pt]{article} +% \usepackage{acl2000} +% \title{Title} +% \author{Author 1 \and Author 2 \\ Address line \\ Address line \And +% Author 3 \\ Address line \\ Address line} +% \begin{document} +% ... +% \bibliography{bibliography-file} +% \bibliographystyle{acl} +% \end{document} + +% Author information can be set in various styles: +% For several authors from the same institution: +% \author{Author 1 \and ... \and Author n \\ +% Address line \\ ... \\ Address line} +% if the names do not fit well on one line use +% Author 1 \\ {\bf Author 2} \\ ... \\ {\bf Author n} \\ +% For authors from different institutions: +% \author{Author 1 \\ Address line \\ ... \\ Address line +% \And ... \And +% Author n \\ Address line \\ ... \\ Address line} +% To start a seperate ``row'' of authors use \AND, as in +% \author{Author 1 \\ Address line \\ ... \\ Address line +% \AND +% Author 2 \\ Address line \\ ... \\ Address line \And +% Author 3 \\ Address line \\ ... \\ Address line} + +% If the title and author information does not fit in the area allocated, +% place \setlength\titlebox{} right after +% \usepackage{acl2000} +% where can be something larger than 2.25in + +% \typeout{Conference Style for ACL 2000 -- released June 20, 2000} +\typeout{Conference Style for ACL 2005 -- released Octobe 11, 2004} + +% NOTE: Some laser printers have a serious problem printing TeX output. +% These printing devices, commonly known as ``write-white'' laser +% printers, tend to make characters too light. To get around this +% problem, a darker set of fonts must be created for these devices. +% + +%% % Physical page layout - slightly modified from IJCAI by pj +%% \setlength\topmargin{0.0in} \setlength\oddsidemargin{-0.0in} +%% \setlength\textheight{9.0in} \setlength\textwidth{6.5in} +%% \setlength\columnsep{0.2in} +%% \newlength\titlebox +%% \setlength\titlebox{2.25in} +%% \setlength\headheight{0pt} \setlength\headsep{0pt} +%% %\setlength\footheight{0pt} +%% \setlength\footskip{0pt} +%% \thispagestyle{empty} \pagestyle{empty} +%% \flushbottom \twocolumn \sloppy + +%% Original A4 version of page layout +%% \setlength\topmargin{-0.45cm} % changed by Rz -1.4 +%% \setlength\oddsidemargin{.8mm} % was -0cm, changed by Rz +%% \setlength\textheight{23.5cm} +%% \setlength\textwidth{15.8cm} +%% \setlength\columnsep{0.6cm} +%% \newlength\titlebox +%% \setlength\titlebox{2.00in} +%% \setlength\headheight{5pt} +%% \setlength\headsep{0pt} +%% \setlength\footheight{0pt} +%% \setlength\footskip{0pt} +%% \thispagestyle{empty} +%% \pagestyle{empty} + +% A4 modified by Eneko +\setlength{\paperwidth}{21cm} % A4 +\setlength{\paperheight}{29.7cm}% A4 +\setlength\topmargin{-0.5cm} +\setlength\oddsidemargin{0cm} +\setlength\textheight{24.7cm} +\setlength\textwidth{16.0cm} +\setlength\columnsep{0.6cm} +\newlength\titlebox +\setlength\titlebox{2.00in} +\setlength\headheight{5pt} +\setlength\headsep{0pt} +\thispagestyle{empty} +\pagestyle{empty} + + +\flushbottom \twocolumn \sloppy + +% We're never going to need a table of contents, so just flush it to +% save space --- suggested by drstrip@sandia-2 +\def\addcontentsline#1#2#3{} + +% Title stuff, taken from deproc. +\def\maketitle{\par + \begingroup + \def\thefootnote{\fnsymbol{footnote}} + \def\@makefnmark{\hbox to 0pt{$^{\@thefnmark}$\hss}} + \twocolumn[\@maketitle] \@thanks + \endgroup + \setcounter{footnote}{0} + \let\maketitle\relax \let\@maketitle\relax + \gdef\@thanks{}\gdef\@author{}\gdef\@title{}\let\thanks\relax} +\def\@maketitle{\vbox to \titlebox{\hsize\textwidth + \linewidth\hsize \vskip 0.125in minus 0.125in \centering + {\Large\bf \@title \par} \vskip 0.2in plus 1fil minus 0.1in + {\def\and{\unskip\enspace{\rm and}\enspace}% + \def\And{\end{tabular}\hss \egroup \hskip 1in plus 2fil + \hbox to 0pt\bgroup\hss \begin{tabular}[t]{c}\bf}% + \def\AND{\end{tabular}\hss\egroup \hfil\hfil\egroup + \vskip 0.25in plus 1fil minus 0.125in + \hbox to \linewidth\bgroup\large \hfil\hfil + \hbox to 0pt\bgroup\hss \begin{tabular}[t]{c}\bf} + \hbox to \linewidth\bgroup\large \hfil\hfil + \hbox to 0pt\bgroup\hss \begin{tabular}[t]{c}\bf\@author + \end{tabular}\hss\egroup + \hfil\hfil\egroup} + \vskip 0.3in plus 2fil minus 0.1in +}} + +% margins for abstract +\renewenvironment{abstract}% + {\centerline{\large\bf Abstract}% + \begin{list}{}% + {\setlength{\rightmargin}{0.6cm}% + \setlength{\leftmargin}{0.6cm}}% + \item[]\ignorespaces}% + {\unskip\end{list}} + +%\renewenvironment{abstract}{\centerline{\large\bf +% Abstract}\vspace{0.5ex}\begin{quote}}{\par\end{quote}\vskip 1ex} + + +% bibliography + +\def\thebibliography#1{\section*{References} + \global\def\@listi{\leftmargin\leftmargini + \labelwidth\leftmargini \advance\labelwidth-\labelsep + \topsep 1pt plus 2pt minus 1pt + \parsep 0.25ex plus 1pt \itemsep 0.25ex plus 1pt} + \list {[\arabic{enumi}]}{\settowidth\labelwidth{[#1]}\leftmargin\labelwidth + \advance\leftmargin\labelsep\usecounter{enumi}} + \def\newblock{\hskip .11em plus .33em minus -.07em} + \sloppy + \sfcode`\.=1000\relax} + +\def\@up#1{\raise.2ex\hbox{#1}} + +% most of cite format is from aclsub.sty by SMS + +% don't box citations, separate with ; and a space +% also, make the penalty between citations negative: a good place to break +% changed comma back to semicolon pj 2/1/90 +% \def\@citex[#1]#2{\if@filesw\immediate\write\@auxout{\string\citation{#2}}\fi +% \def\@citea{}\@cite{\@for\@citeb:=#2\do +% {\@citea\def\@citea{;\penalty\@citeseppen\ }\@ifundefined +% {b@\@citeb}{{\bf ?}\@warning +% {Citation `\@citeb' on page \thepage \space undefined}}% +% {\csname b@\@citeb\endcsname}}}{#1}} + +% don't box citations, separate with ; and a space +% Replaced for multiple citations (pj) +% don't box citations and also add space, semicolon between multiple citations +\def\@citex[#1]#2{\if@filesw\immediate\write\@auxout{\string\citation{#2}}\fi + \def\@citea{}\@cite{\@for\@citeb:=#2\do + {\@citea\def\@citea{; }\@ifundefined + {b@\@citeb}{{\bf ?}\@warning + {Citation `\@citeb' on page \thepage \space undefined}}% + {\csname b@\@citeb\endcsname}}}{#1}} + +% Allow short (name-less) citations, when used in +% conjunction with a bibliography style that creates labels like +% \citename{, } +% +\let\@internalcite\cite +\def\cite{\def\citename##1{##1, }\@internalcite} +\def\shortcite{\def\citename##1{}\@internalcite} +\def\newcite{\def\citename##1{{\frenchspacing##1} (}\@internalciteb} + +% Macros for \newcite, which leaves name in running text, and is +% otherwise like \shortcite. +\def\@citexb[#1]#2{\if@filesw\immediate\write\@auxout{\string\citation{#2}}\fi + \def\@citea{}\@newcite{\@for\@citeb:=#2\do + {\@citea\def\@citea{;\penalty\@m\ }\@ifundefined + {b@\@citeb}{{\bf ?}\@warning + {Citation `\@citeb' on page \thepage \space undefined}}% +{\csname b@\@citeb\endcsname}}}{#1}} +\def\@internalciteb{\@ifnextchar [{\@tempswatrue\@citexb}{\@tempswafalse\@citexb[]}} + +\def\@newcite#1#2{{#1\if@tempswa, #2\fi)}} + +\def\@biblabel#1{\def\citename##1{##1}[#1]\hfill} + +%%% More changes made by SMS (originals in latex.tex) +% Use parentheses instead of square brackets in the text. +\def\@cite#1#2{({#1\if@tempswa , #2\fi})} + +% Don't put a label in the bibliography at all. Just use the unlabeled format +% instead. +\def\thebibliography#1{\vskip\parskip% +\vskip\baselineskip% +\def\baselinestretch{1}% +\ifx\@currsize\normalsize\@normalsize\else\@currsize\fi% +\vskip-\parskip% +\vskip-\baselineskip% +\section*{References\@mkboth + {References}{References}}\list + {}{\setlength{\labelwidth}{0pt}\setlength{\leftmargin}{\parindent} + \setlength{\itemindent}{-\parindent}} + \def\newblock{\hskip .11em plus .33em minus -.07em} + \sloppy\clubpenalty4000\widowpenalty4000 + \sfcode`\.=1000\relax} +\let\endthebibliography=\endlist + +% Allow for a bibliography of sources of attested examples +\def\thesourcebibliography#1{\vskip\parskip% +\vskip\baselineskip% +\def\baselinestretch{1}% +\ifx\@currsize\normalsize\@normalsize\else\@currsize\fi% +\vskip-\parskip% +\vskip-\baselineskip% +\section*{Sources of Attested Examples\@mkboth + {Sources of Attested Examples}{Sources of Attested Examples}}\list + {}{\setlength{\labelwidth}{0pt}\setlength{\leftmargin}{\parindent} + \setlength{\itemindent}{-\parindent}} + \def\newblock{\hskip .11em plus .33em minus -.07em} + \sloppy\clubpenalty4000\widowpenalty4000 + \sfcode`\.=1000\relax} +\let\endthesourcebibliography=\endlist + +\def\@lbibitem[#1]#2{\item[]\if@filesw + { \def\protect##1{\string ##1\space}\immediate + \write\@auxout{\string\bibcite{#2}{#1}}\fi\ignorespaces}} + +\def\@bibitem#1{\item\if@filesw \immediate\write\@auxout + {\string\bibcite{#1}{\the\c@enumi}}\fi\ignorespaces} + +% sections with less space +\def\section{\@startsection {section}{1}{\z@}{-2.0ex plus + -0.5ex minus -.2ex}{1.5ex plus 0.3ex minus .2ex}{\large\bf\raggedright}} +\def\subsection{\@startsection{subsection}{2}{\z@}{-1.8ex plus + -0.5ex minus -.2ex}{0.8ex plus .2ex}{\normalsize\bf\raggedright}} +%% changed by KO to - values to get teh initial parindent right +\def\subsubsection{\@startsection{subsubsection}{3}{\z@}{-1.5ex plus + -0.5ex minus -.2ex}{0.5ex plus .2ex}{\normalsize\bf\raggedright}} +\def\paragraph{\@startsection{paragraph}{4}{\z@}{1.5ex plus + 0.5ex minus .2ex}{-1em}{\normalsize\bf}} +\def\subparagraph{\@startsection{subparagraph}{5}{\parindent}{1.5ex plus + 0.5ex minus .2ex}{-1em}{\normalsize\bf}} + +% Footnotes +\footnotesep 6.65pt % +\skip\footins 9pt plus 4pt minus 2pt +\def\footnoterule{\kern-3pt \hrule width 5pc \kern 2.6pt } +\setcounter{footnote}{0} + +% Lists and paragraphs +\parindent 1em +\topsep 4pt plus 1pt minus 2pt +\partopsep 1pt plus 0.5pt minus 0.5pt +\itemsep 2pt plus 1pt minus 0.5pt +\parsep 2pt plus 1pt minus 0.5pt + +\leftmargin 2em \leftmargini\leftmargin \leftmarginii 2em +\leftmarginiii 1.5em \leftmarginiv 1.0em \leftmarginv .5em \leftmarginvi .5em +\labelwidth\leftmargini\advance\labelwidth-\labelsep \labelsep 5pt + +\def\@listi{\leftmargin\leftmargini} +\def\@listii{\leftmargin\leftmarginii + \labelwidth\leftmarginii\advance\labelwidth-\labelsep + \topsep 2pt plus 1pt minus 0.5pt + \parsep 1pt plus 0.5pt minus 0.5pt + \itemsep \parsep} +\def\@listiii{\leftmargin\leftmarginiii + \labelwidth\leftmarginiii\advance\labelwidth-\labelsep + \topsep 1pt plus 0.5pt minus 0.5pt + \parsep \z@ \partopsep 0.5pt plus 0pt minus 0.5pt + \itemsep \topsep} +\def\@listiv{\leftmargin\leftmarginiv + \labelwidth\leftmarginiv\advance\labelwidth-\labelsep} +\def\@listv{\leftmargin\leftmarginv + \labelwidth\leftmarginv\advance\labelwidth-\labelsep} +\def\@listvi{\leftmargin\leftmarginvi + \labelwidth\leftmarginvi\advance\labelwidth-\labelsep} + +\abovedisplayskip 7pt plus2pt minus5pt% +\belowdisplayskip \abovedisplayskip +\abovedisplayshortskip 0pt plus3pt% +\belowdisplayshortskip 4pt plus3pt minus3pt% + +% Less leading in most fonts (due to the narrow columns) +% The choices were between 1-pt and 1.5-pt leading +\def\@normalsize{\@setsize\normalsize{11pt}\xpt\@xpt} +\def\small{\@setsize\small{10pt}\ixpt\@ixpt} +\def\footnotesize{\@setsize\footnotesize{10pt}\ixpt\@ixpt} +\def\scriptsize{\@setsize\scriptsize{8pt}\viipt\@viipt} +\def\tiny{\@setsize\tiny{7pt}\vipt\@vipt} +\def\large{\@setsize\large{14pt}\xiipt\@xiipt} +\def\Large{\@setsize\Large{16pt}\xivpt\@xivpt} +\def\LARGE{\@setsize\LARGE{20pt}\xviipt\@xviipt} +\def\huge{\@setsize\huge{23pt}\xxpt\@xxpt} +\def\Huge{\@setsize\Huge{28pt}\xxvpt\@xxvpt} diff --git a/papers/2010_gems_lpsa/acl2010.tex b/papers/2010_gems_lpsa/acl2010.tex new file mode 100644 index 00000000..6377279e --- /dev/null +++ b/papers/2010_gems_lpsa/acl2010.tex @@ -0,0 +1,390 @@ +% +% File acl2010.tex +% +% Contact jshin@csie.ncnu.edu.tw or pkoehn@inf.ed.ac.uk +%% +%% Based on the style files for ACL-IJCNLP-2009, which were, in turn, +%% based on the style files for EACL-2009 and IJCNLP-2008... + +%% Based on the style files for EACL 2006 by +%%e.agirre@ehu.es or Sergi.Balari@uab.es +%% and that of ACL 08 by Joakim Nivre and Noah Smith + +\documentclass[11pt]{article} +\usepackage{acl2010} +\usepackage{times} +\usepackage{url} +\usepackage{latexsym} +%\setlength\titlebox{6.5cm} % You can expand the title box if you +% really have to + +\title{Instructions for ACL-2010 Proceedings} + +\author{Jing-Shin Chang\\ + National Chi Nan University\\ + Puli, Nantou, Taiwan, ROC.\\ + {\tt jshin@csie.ncnu.edu.tw} \And + Philipp Koehn\\ + University of Edinburgh\\ + Edinburgh, United Kingdom\\ + {\tt pkoehn@inf.ed.ac.uk}} + +\date{} + +\begin{document} +\maketitle +\begin{abstract} + This document contains the instructions for preparing a camera-ready + manuscript for the proceedings of ACL-2010. The document itself + conforms to its own specifications, and is therefore an example of + what your manuscript should look like. These instructions should be used for both + papers submitted for review and for final versions of accepted + papers. Authors are asked to conform + to all the directions reported in this document. +\end{abstract} + +\section{Credits} + +This document has been adapted from the instructions for ACL-IJCNLP-2009 +proceedings, by Jing-Shin Chang and Regina Barzilay. +Instructions for those proceedings were in turn +based on the formats of earlier ACL and EACL Conference +proceedings. Those versions were written by several persons, including +John Chen, Henry S. Thompson and Donald Walker. + +\section{Introduction} + +The following instructions are directed to authors of papers submitted +to ACL-2010 or accepted +for publication in its proceedings. All authors are required +to adhere to these specifications. Authors are required to provide a +Portable Document Format (PDF) +% das: removed reference to PostScript +% and PostScript +version of their papers. \textbf{The proceedings will be printed on A4 + paper}. Authors from countries in which access to word-processing +systems is limited should contact the publication chairs Jing-Shin Chang +(\texttt{jshin@csie.ncnu.edu.tw}) and Philipp Koehn +(\texttt{pkoehn@inf.ed.ac.uk}) as soon as possible. + +\section{General Instructions} + +Manuscripts must be in two-column format. Exceptions to the +two-column format include the title, authors' names and complete +addresses, which must be centered at the top of the first page, and +any full-width figures or tables (see the guidelines in +Subsection~\ref{ssec:first}). {\bf Type single-spaced.} Start all +pages directly under the top margin. See the guidelines later +regarding formatting the first page. The manuscript should be +printed single-sided and its length +should not exceed the maximum page limit described in Section~\ref{sec:length}. + +\subsection{Electronically-available resources} + +ACL-2010 provides this description in \LaTeX2e (acl2010.tex) and PDF +format (acl2010.pdf), along with the \LaTeX2e style file used to +format it (acl2010.sty) and an ACL bibliography style +(acl.bst). These files are all available at +\url{http://nlp.csie.ncnu.edu.tw/~shin/acl2010/publication/doc/stylefiles/}. A Microsoft Word +template file (acl2010.dot) is also available at the same URL. We +strongly recommend the use of these style files, which have been +appropriately tailored for the ACL-2010 proceedings. If you have an +option, we recommend that you use the \LaTeX2e version. \textbf{If you will be +using the Microsoft Word template, we suggest that you anonymize your +source file so that the pdf produced does not retain your identity.} +This can be done by removing any personal information from your source +document properties. + + + +\subsection{Format of Electronic Manuscript} +\label{sect:pdf} + +For the production of the electronic manuscript you must use Adobe's +Portable Document Format (PDF). This format can be generated from +postscript files. On Linux/Unix systems, you can use {\tt ps2pdf} for +this purpose. In Microsoft Windows, you can use Adobe's Distiller +or GSview (File$<$Convert$<$pdfwrite); if you have \textit{cygwin} +installed, you can use \textit{dvipdf} or \textit{ps2pdf}. Note that +some word processing programs generate PDF which may not include all +the necessary fonts (esp. tree diagrams, symbols). When you print or +create the PDF file, there is usually an option in your printer setup +to include none, all or just non-standard fonts. Please make sure +that you select the option of including ALL the fonts. {\em Before +sending it, test your PDF by printing it from a computer different +from the one where it was created.} Moreover, some word processors may +generate very large postscript/PDF files, where each page is rendered +as an image. Such images may reproduce poorly. In this case, try +alternative ways to obtain the postscript and/or PDF. One way on some +systems is to install a driver for a postscript printer, send your +document to the printer specifying ``Output to a file'', then convert +the file to PDF. + +It is of utmost importance to specify the A4 format (21 cm +x 29.7 cm) when formatting the paper. When working with +{\tt dvips}, for instance, one should specify {\tt -t a4}. + +Print-outs of the PDF file on A4 paper should be identical to the +hardcopy version. If you cannot meet the above requirements about the +production of your electronic submission, please contact the +publication chairs above as soon as possible. + + +\subsection{Layout} +\label{ssec:layout} + +Format manuscripts two columns to a page, in the manner these +instructions are formatted. The exact dimensions for a page on A4 +paper are: + +\begin{itemize} +\item Left and right margins: 2.5 cm +\item Top margin: 2.5 cm +\item Bottom margin: 2.5 cm +\item Column width: 7.7 cm +\item Column height: 24.7 +\item Gap between columns: 0.6 cm +\end{itemize} + +Papers should not be formatted for any other paper size. +% Removed by KO we are not accepting printed papers any more!!! +% Exceptionally, +% authors for whom it is \emph{impossible} to print on A4 paper may use +% \emph{US Letter} paper. In this case, they should keep the \emph{top} +% and \emph{left} margins as given above, use the same column width, +% height and gap, and modify the bottom and right margins as +% necessary. Note that the text will no longer be centered. + +\subsection{Fonts} + +For reasons of uniformity, Adobe's {\bf Times Roman} font should be +used. In \LaTeX2e{} this is accomplished by putting + +\begin{quote} +\begin{verbatim} +\usepackage{times} +\usepackage{latexsym} +\end{verbatim} +\end{quote} +in the preamble. If Times Roman is unavailable, use {\bf Computer + Modern Roman} (\LaTeX2e{}'s default). Note that the latter is about + 10\% less dense than Adobe's Times Roman font. + + +\begin{table}[h] +\begin{center} +\begin{tabular}{|l|rl|} +\hline \bf Type of Text & \bf Font Size & \bf Style \\ \hline +paper title & 15 pt & bold \\ +author names & 12 pt & bold \\ +author affiliation & 12 pt & \\ +the word ``Abstract'' & 12 pt & bold \\ +section titles & 12 pt & bold \\ +document text & 11 pt &\\ +captions & 11 pt & \\ +abstract text & 10 pt & \\ +bibliography & 10 pt & \\ +footnotes & 9 pt & \\ +\hline +\end{tabular} +\end{center} +\caption{\label{font-table} Font guide. } +\end{table} + +\subsection{The First Page} +\label{ssec:first} + +Center the title, author's name(s) and affiliation(s) across both +columns. Do not use footnotes for affiliations. Do not include the +paper ID number assigned during the submission process. Use the +two-column format only when you begin the abstract. + +{\bf Title}: Place the title centered at the top of the first page, in +a 15-point bold font. (For a complete guide to font sizes and styles, see Table~\ref{font-table}.) Long titles should be typed on two lines without +a blank line intervening. Approximately, put the title at 2.5 cm from +the top of the page, followed by a blank line, then the author's +names(s), and the affiliation on the following line. Do not use only +initials for given names (middle initials are allowed). Do not format surnames +in all capitals (e.g., use ``Schlangen'' not ``SCHLANGEN''). +Do not format title and section headings in all capitals as well +except for proper names (such as ``BLEU'') that are conventionally +in all capitals. +The affiliation should contain the author's complete address, and if +possible, an electronic mail address. Leave about 2 cm between the +affiliation and the body of the first page. +The title, author names and addresses should be completely +identical to those entered to the electronical paper submission +website in order to maintain the consistency of author information +among all publications of the conference. + +{\bf Abstract}: Type the abstract at the beginning of the first +column. The width of the abstract text should be smaller than the +width of the columns for the text in the body of the paper by about +0.6 cm on each side. Center the word {\bf Abstract} in a 12 point bold +font above the body of the abstract. The abstract should be a concise +summary of the general thesis and conclusions of the paper. It should +be no longer than 200 words. + +{\bf Text}: Begin typing the main body of the text immediately after +the abstract, observing the two-column format as shown in +the present document. + +{\bf Indent} when starting a new paragraph. Use 11 points for text and +subsection headings, 12 points for section headings and 15 points for +the title. + +\subsection{Sections} + +{\bf Headings}: Type and label section and subsection headings in the +style shown on the present document. Use numbered sections (Arabic +numerals) in order to facilitate cross references. Number subsections +with the section number and the subsection number separated by a dot, +in Arabic numerals. + +{\bf Citations}: Citations within the text appear +in parentheses as~\cite{Gusfield:97} or, if the author's name appears in +the text itself, as Gusfield~\shortcite{Gusfield:97}. +Append lowercase letters to the year in cases of ambiguity. +Treat double authors by using both authors' last names (e.g., +\cite{Aho:72}, but use \emph{et al.} when more than two authors are +involved. (e.g. \cite{Chandra:81}) +Collapse multiple citations (e.g., \cite{Gusfield:97,Aho:72}.) Also +refrain from using full citations as sentence constituents. We suggest +that instead of +\begin{quote} + ``\cite{Gusfield:97} showed that ...'' +\end{quote} +you use +\begin{quote} +``Gusfield \shortcite{Gusfield:97} showed that ...'' +\end{quote} + +If you are using the provided \LaTeX{} and Bib\TeX{} style files, you +can use the command \verb|\newcite| to get ``author (year)'' citations. + +As reviewing will be double-blind, the submitted version of the papers should not include the +authors' names and affiliations. Furthermore, self-references that +reveal the author's identity, e.g., +\begin{quote} +``We previously showed \cite{Gusfield:97} ...'' +\end{quote} +should be avoided. Instead, use citations such as +\begin{quote} +``Gusfield \shortcite{Gusfield:97} +previously showed ... '' +\end{quote} + +Please do not use anonymous +citations and do not include acknowledgements when submitting your papers. Papers that do not conform +to these requirements may be rejected without review. + +\textbf{References}: Gather the full set of references together under +the heading {\bf References}; place the section before any Appendices, +unless they contain references. Arrange the references alphabetically +by first author, rather than by order of occurrence in the text. +Provide as complete a citation as possible, using a consistent format, +such as the one for {\em Computational Linguistics\/} or the one in the +{\em Publication Manual of the American +Psychological Association\/}~\cite{APA:83}. Use of full names for +authors rather than initials is preferred. A list of abbreviations +for common computer science journals can be found in the ACM +{\em Computing Reviews\/}~\cite{ACM:83}. + +The \LaTeX{} and Bib\TeX{} style files provided roughly fit the +American Psychological Association format, allowing regular citations, +short citations and multiple citations as described above. + +{\bf Appendices}: Appendices, if any, directly follow the text and the +references (but see above). Letter them in sequence and provide an +informative title: {\bf Appendix A. Title of Appendix}. + +\textbf{Acknowledgement} section should go as a last section immediately +before the references. Do not number the acknowledgement section. + +\subsection{Footnotes} + +{\bf Footnotes}: Put footnotes at the bottom of the page and use 9 +points text. They may be numbered or referred to by asterisks or other +symbols.\footnote{This is how a footnote should appear.} Footnotes +should be separated from the text by a line.\footnote{Note the line +separating the footnotes from the text.} + +\subsection{Graphics} + +{\bf Illustrations}: Place figures, tables, and photographs in the +paper near where they are first discussed, rather than at the end, if +possible. Wide illustrations may run across both columns. Color +illustrations are discouraged, unless you have verified that +they will be understandable when printed in black ink. + +{\bf Captions}: Provide a caption for every illustration; number each one +sequentially in the form: ``Figure 1. Caption of the Figure.'' ``Table 1. +Caption of the Table.'' Type the captions of the figures and +tables below the body, using 11 point text. + +\section{Translation of non-English Terms} + +It is also advised to supplement non-English characters and terms +with appropriate transliterations and/or translations +since not all readers understand all such characters and terms. +Inline transliteration or translation can be represented in +the order of: original-form transliteration ``translation''. + +\section{Length of Submission} +\label{sec:length} + +Long papers may consist of up to 8 pages of content (excluding references), +and short papers may consist of up to 4 pages of content (excluding references). +Both long and short papers may include any additional number of pages consisting +\emph{solely} of references. +(Appendices count against the eight or four pages, not the additional references pages). +All illustrations, references, and appendices must be +accommodated within these page limits, observing the formatting +instructions given in the present document. Papers that do not +conform to the specified length and formatting requirements are +subject to be rejected without review. + + +\section*{Acknowledgments} + +Do not number the acknowledgment section. Do not include this section +when submitting your paper for review. +%\bibliographystyle{acl} +% you bib file should really go here +%\bibliography{acl2010} + +\begin{thebibliography}{} + +\bibitem[\protect\citename{Aho and Ullman}1972]{Aho:72} +Alfred~V. Aho and Jeffrey~D. Ullman. +\newblock 1972. +\newblock {\em The Theory of Parsing, Translation and Compiling}, volume~1. +\newblock Prentice-{Hall}, Englewood Cliffs, NJ. + +\bibitem[\protect\citename{{American Psychological Association}}1983]{APA:83} +{American Psychological Association}. +\newblock 1983. +\newblock {\em Publications Manual}. +\newblock American Psychological Association, Washington, DC. + +\bibitem[\protect\citename{{Association for Computing Machinery}}1983]{ACM:83} +{Association for Computing Machinery}. +\newblock 1983. +\newblock {\em Computing Reviews}, 24(11):503--512. + +\bibitem[\protect\citename{Chandra \bgroup et al.\egroup }1981]{Chandra:81} +Ashok~K. Chandra, Dexter~C. Kozen, and Larry~J. Stockmeyer. +\newblock 1981. +\newblock Alternation. +\newblock {\em Journal of the Association for Computing Machinery}, + 28(1):114--133. + +\bibitem[\protect\citename{Gusfield}1997]{Gusfield:97} +Dan Gusfield. +\newblock 1997. +\newblock {\em Algorithms on Strings, Trees and Sequences}. +\newblock Cambridge University Press, Cambridge, UK. + +\end{thebibliography} + +\end{document} diff --git a/papers/2010_gems_lpsa/gems_lpsa.bib b/papers/2010_gems_lpsa/gems_lpsa.bib new file mode 100644 index 00000000..e5e76daf --- /dev/null +++ b/papers/2010_gems_lpsa/gems_lpsa.bib @@ -0,0 +1,620 @@ +@article{andrews09integrating, + author = {Mark Andrews, Gabriella Vigliocco}, + title = {Integrating Experiential and Distributional Data to Learn Semantic + Representations}, + journal = {Psychological Review}, + volume = 116, + issue = 3, + pages = {463--498}, + year = 2009, +} + +@inproceedings{baroni07isa, + author = {Marco Baroni and Alessandro Lenci and Luca Onnis}, + year = 2007, + title = {ISA meets Lara: A fully incremental word space model for cognitively plausible simulations of semantic learning}, + booktitle = {Proceedings of the 45th Meeting of the Association for Computational Linguistics}, +} + +@article{baroni08concepts, + author = {Marco Baroni and Alessandro Lenci}, + year = 2008, + title = {Concepts and properties in word spaces}, + editor = {Alessandro Lenci}, + journal = {From context to meaning: Distributional models of the lexicon in linguistics and cognitive science (Special issue of the Italian Journal of Linguistics)}, + number = 20, + volume = 1, + pages = {55--88}, +} + +@inproceedings{belkin02laplacian, + author = {Mikhail Belkin and Partha Niyogi}, + title = {Laplacian {E}igenmaps and {S}pectral {T}echniques for {E}mbedding and {C}lustering}, + booktitle = {Advances in Neural Information Processing Systems}, + number = 14, + year = 2002, +} + +@article{bullinaria07extracting, + author = {John A. 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Shiffrin and Douglas L. Nelson}, + title = {Word association spaces for predicting semantic similarity effects in episodic memory}, + booktitle = {Cognitive Psychology and its Applications: Festschrift in Honor of Lyle Bourne}, + editor = {Walter Kintsch and Thomas Landauer}, + year = 2004, + publisher = {American Psychological Assocation}, +} + +@article{tenenbaum00global, + title={A global geometric framework for nonlinear dimensionality reduction}, + author={Joshua B. Tenenbaum and Vin de Silva and John C. Langford}, + journal={Science}, + volume={290}, + number={5500}, + pages={2319--2323}, + year={2000}, + publisher={AAAS} +} + +@article{tibshirani00estimating, + author = {Robert Tibshirani and Guenther Walther and Trevor Hastie}, + title = {Estimating the number of clusters in a dataset via the Gap statistic}, + journal = {Journal Royal Statistics Society B}, + year = {2000}, + volume = {63}, + pages = {411--423} +} + +@inproceedings{turney01mining, + author = {Peter D. Turney}, + year = 2001, + title = {Mining the {W}eb for synonyms: {P}{M}{I}-{I}{R} versus {L}{S}{A} on {T}{O}{E}{F}{L}}, + booktitle = {Proceedings of the Twelfth European Conference on Machine Learning (ECML-2001)}, + location = {Freiburg, Germany}, + pages = {491--502}, +} + +@article{turney06similarity, + author = {Peter D. Turney}, + title = {Similarity of Semantic Relations}, + journal = {Computational Linguistics}, + volume = {32}, + number = {3}, + year = {2006}, + pages = {379--416}, + publisher = {MIT Press}, + address = {Cambridge, MA, USA}, +} + +@article{tversky77features, + author = {Amos Tversky}, + title = {Features of similarity}, + journal = {Psychological Review}, + volume = 84, + pages = {327--352}, + year = 1977, +} + +@inproceedings{weeds04characterising, + author = {Julie Weeds and David Weir and Diana McCarty}, + year = 2004, + title = {Characterising measures of lexical distributional similarity}, + booktitle = {Proceedings of the 20th International Conference on Computational Linguistics COLING'04}, + pages = {1015--1021}, +} + +@inproceedings{widdows08semantic, + author = {Dominic Widdows and Kathleen Ferraro}, + title = {Semantic Vectors: a Scalable Open Source Package and Online Technology Management Application}, + booktitle = {Proceedings of the Sixth International Language Resources and Evaluation (LREC'08)}, + year = {2008}, +} + diff --git a/papers/2010_gems_lpsa/gems_lpsa.tex b/papers/2010_gems_lpsa/gems_lpsa.tex new file mode 100644 index 00000000..8bebfc4b --- /dev/null +++ b/papers/2010_gems_lpsa/gems_lpsa.tex @@ -0,0 +1,571 @@ +\documentclass[11pt]{article} +\usepackage{acl2010} +\usepackage{times} +\usepackage{url} +\usepackage{latexsym} +\usepackage{epsfig} +\usepackage{latexsym} +\usepackage[usenames]{color} +\usepackage{times} +\usepackage{verbatim} +\usepackage{multirow} +\usepackage{threeparttable} +\usepackage{booktabs} +\usepackage{amsfonts} +\usepackage{amsmath} +\usepackage{amssymb} + +\newcommand{\argmin}{\operatornamewithlimits{argmin}} + +\title{Capturing Nonlinear Structure in Word Spaces Through Dimensionality + Reduction } + +\author{ David Jurgens\\ + University of California, Los Angeles, \\ + 4732 Boelter Hall \\ + Los Angeles, CA 90095 \\ + {\tt jurgens@cs.ucla.edu} \And + Keith Stevens\\ + University of California, Los Angeles, \\ + 4732 Boelter Hall \\ + Los Angeles, CA 90095 \\ + {\tt kstevens@cs.ucla.edu}} + +\date{} + +\begin{document} +\maketitle + +\begin{abstract} +Dimensionality reduction has been shown to improve processing and information +extraction from high dimensional data. +% +Word space algorithms typically employ linear reduction techniques that assume +the space is Euclidean. We investigate the effects of extracting nonlinear +structure in the word space using Locality Preserving Projections, a reduction +algorithm that performs manifold learning. We apply this reduction to two common +word space models and show improved performance over the original models on +benchmarks. +\end{abstract} + + +\section{Introduction} + +Vector space models of semantics frequently employ some form of dimensionality +reduction for improvement in representations or computational overhead. +Many of the dimensionality reduction algorithms assume that the unreduced word +space is linear. However, word similarities have been shown to exhibit many +non-metric properties: asymmetry, e.g North Korea is more similar to Red China +than Red China is to North Korea, and non-transitivity, e.g. Cuba is similar the +former USSR, Jamaica is similar to Cuba, but Jamaica is not similar to the USSR +\cite{tversky77features}. We hypothesize that a non-linear word space model +might more accurately preserve these non-metric relationships. + +To test our hypothesis, we capture the non-linear structure with dimensionality +reduction by using Locality Preserving Projection (LPP) \cite{he03locality}, an +efficient, linear approximation of Eigenmaps \cite{belkin02laplacian}. +With this reduction, the word space vectors are assumed to exist on a nonlinear +manifold that LPP learns in order to project the vectors into a Euclidean space. +We measure the effects of using LPP on two basic word space models: the Vector +Space Model and a Word Co-occurrence model. We begin with a brief overview of +these word spaces and common dimensionality reduction techniques. We then +formally introduce LPP. Following, we use two experiments to demonstrate LPP's +capacity to accurately dimensionally reduce word spaces. + +\section{Word Spaces and Reductions} +\label{sec:dim} + +We consider two common word space models that have been used with dimensionality +reduction. The first is the Vector Space Model (VSM) \cite{salton75vector}. +Words are represented as vectors where each dimension corresponds to a document +in the corpus and the dimension's value is the number of times the word occurred +in the document. We label the second model the Word Co-occurrence (WC) model: +each dimension correspond to a unique word, with the dimension's value +indicating the number of times that dimension's word co-occurred. + +Dimensionality reduction has been applied to both models for three kinds of +benefits: to improve computational efficiency, to capture higher order +relationships between words, and to reduce noise by smoothing or eliminating +noisy features. We consider three of the most popular reduction techniques and +the general word space models to which they have been applied: linear +projections, feature elimination and random approximations. + +The most frequently applied linear projection technique is the Singular Value +Decomposition (SVD). The SVD factors a matrix $A$, which represents a word +space, into three matrices $U \Sigma V^\top$ such that $\Sigma$ is a diagonal +matrix containing the singular values of $A$, ordered descending based on their +effect on the variance in the values of $A$. The original matrix can be +approximated by using only the top $k$ singular values, setting all others to 0. +The approximation matrix, $\hat{A} = U_k \Sigma_k V_k^{\top}$, is the least +squares best-fit rank-$k$ approximation of $A$. + +The SVD has been used with great success on both models. Latent Semantic +Analysis (LSA) \cite{landauer97solution} extends the (VSM) by decomposing the +space using the SVD and making the word space the left singular vectors, $U_k$. +WC models have also utilized the SVD to improve performance % by data smoothing +\cite{schutze92dimensions,bullinaria07extracting,baroni08concepts}. + +Feature elimination reduces the dimensionality by removing those with low +information content. This approach has been successfully applied to WC models +such as HAL \cite{lund96producing} by dropping those with low entropy. This +technique effectively removes the feature dimensions of high frequency words, +which provide little discriminatory content. + +Randomized projections have also been successfully applied to VSM models, e.g. +\cite{kanerva00random} and WC models, e.g. \cite{sahlgren08permutations}. This +reduction statistically approximates the original space in a much lower +dimensional space. The projection does not take into account the structure +of data, which provides only a computational benefit from fewer dimensions, +unlike the previous two reductions. + +\section{Locality Preserving Projection} +\label{sec:lpp} +For a set of vectors, $x_1, x_2, \ldots, x_n \in \mathbb{R}^m$, LPP preserves the +distance in the $k$-dimensional space, where $k \ll m$, by solving the following +minimization problem, +\begin{equation} + \min_w \sum_{ij}({\bf w}^{\top}{\bf x}_i - {\bf w}^{\top}{\bf x}_j)^{2}S_{ij} +\end{equation} +where ${\bf w}$ is a transformation vector that projects ${\bf x}$ into the lower +dimensional space, and $S$ is a matrix that represents the local structure of +the original space. Minimizing this equation is equivalent to finding the +transformation vector that best preserves the local distances in the original +space according to $S$. LPP assumes that the data points ${\bf x}_i$ exist on a +manifold. This is in contrast to the SVD, which assumes that the space is +Euclidean and performs a global, rather than local, minimization. In treating +the space as a manifold, LPP is able to discover some of the nonlinear structure +of the data from its local structure. + + +To solve the minimization problem in Equation 1, LPP uses a linear approximation +of the Laplacian Eigenmaps procedure \cite{belkin02laplacian} as follows: +\begin{enumerate} + \setlength{\itemsep}{1pt} + \setlength{\parskip}{0pt} + \setlength{\parsep}{0pt} + \item Let $X$ be a matrix where ${\bf x}_i$ is the $i^{th}$ row vector. Construct an + adjacency matrix, $S$, which represents the local structure of the original + vector space, by making an edge between points ${\bf x}_i$ and ${\bf x}_j$ + if ${\bf x}_j$ is locally proximate to ${\bf x}_i$. Two variations are + available for determining proximity: either the $k$-nearest neighbors, or + all the data points with similarity $ > \epsilon$. + % Two sentences were turned into one. + + \item Weight the edges in $S$ proportional to the closeness of the data + points. Four main options are available: a Gaussian kernel, a polynomial + kernel, cosine similarity, or binary % (i.e. no weighting). + + \item Construct the diagonal matrix $D$ where entry $D_{ii} = \sum_j + S_{ij}$. Let $L = D - S$. Then solve the generalized eigenvector problem: + \begin{equation} + XLX^{\top}{\bf w} = \lambda XDX^{\top}{\bf w}. + \end{equation} + He and Niyogi \shortcite{he03locality} show that solving this problem is + equivalent to solving Equation 1. + + \item Let $W_k$ = $[{\bf w}_1, \ldots, {\bf w}_k]$ denote the matrix of + transformation vectors, sorted in descending order according to their + eigenvalues $\lambda$. The original space is projected into $k$ dimensions + by $W_k^{\top}X \rightarrow X_k$. +\end{enumerate} + +For many applications of LPP, such as document clustering \cite{he04locality}, +the original data matrix $X$ is transformed by first performing Principle +Component Analysis and discarding the smallest principle components, which +requires computing the full SVD. However, for large data sets such as those +frequently used in word space algorithms, performing the full SVD is +computationally infeasible. + +To overcome this limitation, Cai et al. \shortcite{cai07spectral} show how +Spectral Regression may be used as an alternative for solving the same +minimization equation through an iterative process. The principle idea is that +Equation 2 may be recast as +\begin{equation} + S{\bf y} = \lambda D {\bf y} +\end{equation} +where ${\bf y}=X^{\top}{\bf w}$, which ensures $\bf y$ will be an eigenvector +with the same eigenvalue for the problem in Equation 2. Finding the +transformation matrix $W_k$, used in step 4, is done in two steps. First, +Equation 3 is solved to produce eigenvectors $[ {\bf y}_0, \ldots, {\bf y}_k]$, +sorted in decreasing order according to their eigenvalues $\lambda$. Second, +the set of transformation vectors composing $W_k$, $[{\bf w}_1,\ldots, {\bf +w}_k]$, is found by a least-squares regression: +\begin{equation} + {\bf w}_j = \argmin_{\bf w} \sum^{n}_{i=1}({\bf w}^{\top}{\bf x}_i - {\bf y}_i^j)^2 + + \alpha||{\bf w}||^2 +\end{equation} +where +${\bf y}_i^j$ denotes the +value of the $j^{th}$ dimension of ${\bf y}_i$. The $\alpha$ value is a +regularization parameter that penalizes solutions proportionally to their +magnitude; Cai et al. \shortcite{cai07regularized} note when minimizing, if +there are fewer data points than dimensions, this parameter is needed to ensure +the stability of ${\bf w}$ as an approximate solution to the eigenproblem. + + +\section{Experiments} +\label{sec:experiments} + +Two experiments measures the effects of nonlinear dimensionality reduction for +word spaces. For both, we apply LPP to two basic word space models, the VSM and +WC. In the first experiment, we measure the word spaces' abilities to model +semantic relations, as determined by priming experiments. In the second +experiment, we evaluate the representation capabilities of the LPP-reduced +models on standard word space benchmarks. + +\subsection{Setup} + +For the VSM-based word space, we consider three different weighting schemes: no +weighting, TF-IDF and the log-entropy (LE) used in \cite{landauer97solution}. +For the WC-based word space, we use a 5 word sliding window. In all +experiments the affinity matrix is built using the 20 nearest neighbors +according to cosine similarity in the original word space, with the cosine +similarity as the weight of each link. We reduce all LPP-based spaces to 300 +dimensions, based on empirical analysis. Stop words were removed only for the +WC+LPP model. +We compare the LPP-based spaces to three models: VSM, HAL, and LSA. + +Two corpora are used to train the models in both experiments. The first corpus, +TASA, is a collection of 44,486 essays that are representative of the reading +a student might see upon entering college, introduced by +\cite{landauer97solution}. The corpus consists of 98,420 unique words; no +filtering is done when processing this corpus. The second corpus, WIKI, is a +387,082 article subset of a December 2009 Wikipedia snapshot consisting of all +the articles with more than 1,000 tokens. The corpus is filtered to retain +the top 100,000 most frequent tokens in addition to all the tokens used in +each experiment's data set. + +\subsection{Experiment 1} + +We use data from semantic priming studies to evaluate LPP based word spaces, +which are well studied psychological tests that demonstrate a facilitating +connection between words and have been used to evaluate word space +representations \cite{pado07dependency}. We use two priming tests to evaluate +LPP's ability to model the semantic relationships measured by priming. + +\paragraph{Normed Priming} Nelson et al. \shortcite{nelson98word} collected +free association responses to 5,019 prime words. An average of 149 participants +responded to each prime with the first word that came to mind. + +Based on this dataset, we introduce a new benchmark that correlates word space +similarity with the associative strength of semantic priming pairs. We use +three measures for modeling prime-target strength, which were inspired by +Steyvers et al. \shortcite{steyvers04word}. Let $W_{ab}$ be the percentage of +participants who responded to prime $a$ with target $b$. The three measures of +associative strength are +\[ +\begin{array}{l} +S^1_{ab} = W_{ab} \\ +S^2_{ab} = W_{ab} + W_{ba} \\ +S^3_{ab} = S^2_{ab} + \sum_c S^2_{ac} S^2_{cb} +\end{array} +\] +These measure three different levels of semantic relatedness between words $a$ +and $b$. $S^1_{ab}$ measures the relationship from $a$ to $b$, which is +frequently asymmetric due to ordering, e.g. ``orange'' produces ``juice'' more +frequently than ``juice'' produces ``orange.'' $S^2_{ab}$ measures the +symmetric association between $a$ and $b$; Steyvers et +al. \shortcite{steyvers04word} note that this may better model the associative +strength by including weaker associates that may have been a suitable second +response. $S^3_{ab}$ further increases the association by including the +indirect associations between $a$ and $b$ from all cued primes. + +For each measure, we rank a prime's targets according to their strength and then +compute the Spearman rank correlation with the prime-target similarities in the +word space. The rank comparison measures how well word space similarity +corresponds to the priming association. We report the average rank correlation +of associational strengths over all primes. + +\begin{table*}[htb] + \center + \small + \begin{threeparttable} + \begin{tabular}{l ccc r ccc r ccc } + \toprule + & + \multicolumn{3}{c}{Antonymy} && + \multicolumn{3}{c}{Conceptual} && + \multicolumn{3}{c}{Coordinates} \\ + \cmidrule{2-4} \cmidrule{6-8} \cmidrule{10-12} + Algorithm & R\tnote{b} & U & E && R & U & E && R & U & E \\ + \midrule + VSM+LPP+LE & 0.103 & 0.018 & 0.085 && 0.197 & 0.050 & 0.147 && 0.071 & 0.027 & 0.044 \\ + VSM+LPP+TF-IDF & + 0.348 & 0.321 & 0.027 && 0.408 & 0.414 & -0.005 && 0.323 & 0.294 & 0.029 \\ + VSM+LPP & + 0.247 & 0.122 & 0.124 && 0.312 & 0.120 & 0.193 && 0.230 & 0.111 & 0.119 \\ + VSM+LPP\tnote{a} & + 0.298 & 0.070 & {\bf 0.228} && 0.284 & 0.033 & 0.252 && 0.321 & 0.037 & {\bf + 0.284} \\ + WC+LPP & + 0.255 & 0.071 & 0.185 && 0.413 & 0.110 & 0.303 && 0.431 & 0.134 & {\bf 0.298} \\ + HAL & + 0.813 & 0.716 & 0.096 && 0.845 & 0.814 & 0.031 && 0.861 & 0.809 & 0.052 \\ + HAL\tnote{a} & + 0.915 & 0.879 & 0.037 && 0.867 & 0.846 & 0.021 && 0.913 & 0.861 & 0.052 \\ + LSA & + 0.235 & 0.023 & 0.213 && 0.392 & 0.028 & {\bf 0.364} && 0.199 & 0.014 & 0.185 \\ + LSA\tnote{a} & + 0.287 & 0.061 & 0.226 && 0.362 & 0.041 & 0.321 && 0.316 & 0.037 & 0.278 \\ + VSM & + 0.051 & 0.011 & 0.040 && 0.111 & 0.012 & 0.099 && 0.032 & 0.008 & 0.024 \\ + + DV & +0.703 & 0.494 & 0.210 && 0.736 & 0.701 & 0.035 && 0.779 & 0.682 & 0.096 \\ + DV-max & +0.703 & 0.494 & 0.210 && 0.736 & 0.701 & 0.035 && 0.779 & 0.682 & 0.096 \\ + DV-max-rel & +0.638 & 0.320 & 0.319 && 0.674 & 0.648 & 0.026 && 0.718 & 0.619 & 0.098 \\ + DV-med & +0.703 & 0.494 & 0.210 && 0.736 & 0.701 & 0.035 && 0.779 & 0.682 & 0.096 \\ + DV-med-rel & +0.638 & 0.320 & 0.319 && 0.674 & 0.648 & 0.026 && 0.718 & 0.619 & 0.098 \\ + + \cmidrule{1-12} + & + \multicolumn{3}{c}{Phrasal} && + \multicolumn{3}{c}{Ordinates} && + \multicolumn{3}{c}{Synonymy} \\ + \cmidrule{2-4} \cmidrule{6-8} \cmidrule{10-12} + Algorithm & R & U & E && R & U & E && R & U & E \\ + \midrule + VSM+LPP+LE & + 0.147 & 0.039 & 0.108 && 0.225 & 0.032 & 0.193 && 0.081 & 0.027 & 0.053 \\ + VSM+LPP+TF-IDF & + 0.438 & 0.425 & 0.013 && 0.277 & 0.290 & -0.013 && 0.344 & 0.328 & 0.017 \\ + VSM+LPP & + 0.234 & 0.107 & 0.127 && 0.273 & 0.115 & 0.158 && 0.237 & 0.157 & 0.080 \\ + VSM+LPP\tnote{a} & + 0.202 & 0.031 & 0.171 && 0.270 & 0.032 & 0.238 && 0.299 & 0.069 & 0.230 \\ + WC+LPP & + 0.274 & 0.087 & 0.186 && 0.324 & 0.076 & 0.248 && 0.345 & 0.111 & 0.233 \\ + HAL & + 0.805 & 0.776 & 0.029 && 0.825 & 0.789 & 0.036 && 0.757 & 0.681 & 0.076 \\ + HAL\tnote{a} & + 0.866 & 0.856 & 0.010 && 0.881 & 0.857 & 0.024 && 0.898 & 0.879 & 0.019 \\ + LSA & +0.280 & 0.021 & {\bf 0.258} && 0.258 & 0.018 & 0.240 && 0.197 & 0.019 & 0.178 \\ + LSA\tnote{a} & +0.269 & 0.030 & 0.238 && 0.326 & 0.032 & {\bf 0.294} && 0.327 & 0.052 & {\bf +0.275} \\ + VSM & +0.104 & 0.013 & 0.091 && 0.061 & 0.008 & 0.053 && 0.052 & 0.009 & 0.043 \\ + + DV & +0.519 & 0.517 & 0.002 && 0.771 & 0.718 & 0.053 && 0.703 & 0.534 & 0.170 \\ + DV-max & +0.519 & 0.517 & 0.002 && 0.771 & 0.718 & 0.053 && 0.703 & 0.534 & 0.170 \\ + DV-max-rel & +0.412 & 0.426 & -0.015 && 0.730 & 0.662 & 0.068 && 0.609 & 0.381 & 0.227 \\ + DV-med & +0.519 & 0.517 & 0.002 && 0.771 & 0.718 & 0.053 && 0.703 & 0.534 & 0.170 \\ + DV-med-rel & +0.412 & 0.426 & -0.015 && 0.730 & 0.662 & 0.068 && 0.609 & 0.381 & 0.227 \\ + + + + \bottomrule + + \end{tabular} + \begin{tablenotes} + \item[a] {\footnotesize Processed using the WIKI corpus} + \item[b] {\footnotesize R are related primes, U are unrelated primes, E is + the priming effect} + \end{tablenotes} + \end{threeparttable} + \caption{Experiment 1 priming results for the six relation categories from + Hodgson \shortcite{hodgson91informational}} + \label{tab:categorical-priming-b} +\end{table*} + +\begin{table*}[hbt!f] + \center + \small + \begin{tabular}{l l r ccc r ccc } + \toprule + & & & \multicolumn{3}{c}{Word Choice} & & + \multicolumn{3}{c}{Word Association} \\ + \cmidrule{4-6} \cmidrule{8-10} + Algorithm & Corpus && TOEFL & ESL & RDWP & & F. et al. & R.\&G. & Deese \\ + \midrule + VSM+LPP+le & TASA && 24.000 & 50.000 & 45.313 && + 0.296 & 0.092 & 0.034 \\ + + VSM+LPP+tf-idf & TASA && 22.667 & 25.000 & 37.209 && + 0.023 & 0.086 & 0.001 \\ + + VSM+LPP & TASA && 41.333 & {\bf 54.167} & 39.063 && + 0.219 & 0.136 & 0.045 \\ + + VSM+LPP & Wiki && 33.898 & 48.780 & 43.434 && + 0.530 & 0.503 & 0.108 \\ + + WC+LPP & TASA && 46.032 & 40.000 & 45.783 && + 0.423 & 0.414 & 0.126 \\ + + HAL & TASA && 44.00 & 20.83 & 50.00 && 0.173 & 0.180 & 0.318 \\ + HAL & Wiki && 50.00 & 31.11 & 43.44 && 0.261 & 0.195 & 0.042 \\ + + LSA & TASA && 56.000 & 50.000 & 55.814 && + 0.516 & 0.651 & {\bf 0.349} \\ + + LSA & Wiki && 60.759 & {\bf 54.167} & 59.200 && + {\bf 0.614} & {\bf 0.681} & 0.206 \\ + + VSM & TASA && {\bf 61.333} & 52.083 & {\bf 84.884} && + 0.396 & 0.496 & 0.200 \\ + + DV & PukWac && + 52.941 & 33.333 & 56.410 && 0.161 & 0.337 & \\ + DV-max & PukWac && + 52.941 & 33.333 & 56.410 && 0.161 & 0.337 & \\ + DV-max-rel & PukWac && + 52.941 & 37.778 & 53.846 && 0.180 & 0.263 & \\ + DV-med & PukWac && + 52.941 & 33.333 & 56.410 && 0.161 & 0.337 & \\ + DV-med-rel & PukWac && + 52.941 & 37.778 & 53.846 && 0.180 & 0.263 & \\ + + \bottomrule + \end{tabular} + \caption{Results from Experiment 2 on six word space benchmarks} + \label{tab:exp3} +\end{table*} + + +\begin{table}[bt] + \small + \center + \begin{tabular}{l l ccc } + \toprule + Algorithm & Corpus & $S^1$ & $S^2$ & $S^3$ \\ + \midrule + VSM+LPP+LE & TASA & 0.457 & 0.413 & 0.255 \\ + VSM+LPP+TF-IDF & TASA & 0.464 & 0.390 & 0.207 \\ + VSM+LPP & TASA & 0.457 & 0.427 & 0.275 \\ + VSM+LPP & Wiki & 0.472 & 0.440 & 0.333 \\ + WC+LPP & TASA & 0.469 & 0.437 & 0.315 \\ + + HAL & TASA & 0.485 & 0.434 & 0.310 \\ + HAL & Wiki & 0.462 & 0.406 & 0.266 \\ + LSA & TASA & {\bf 0.494} & {\bf 0.481} & {\bf 0.414} \\ + LSA & Wiki & 0.489 & 0.472 & 0.398 \\ + VSM & TASA & 0.484 & 0.460 & 0.407 \\ + + DV & PukWac & 0.468 & 0.427 & 0.298 \\ + DV-max & PukWac & 0.468 & 0.427 & 0.298 \\ + DV-max-rel & PukWac & 0.470 & 0.432 & 0.302 \\ + DV-med & PukWac & 0.468 & 0.427 & 0.298 \\ + DV-med-rel & PukWac & 0.470 & 0.432 & 0.302 \\ + + \bottomrule + \end{tabular} + \caption{Experiment 1 results for normed priming.} + \label{tab:semantic-priming} +\end{table} + + +\paragraph{Priming Effect} +The priming study by Hodgson \shortcite{hodgson91informational}, which evaluated +how different semantic relationships affected the strength of priming, provides +the data for our second priming test. Six relationships were examined in the +study: antonymy, synonymy, conceptual association (sleep and bed), categorical +coordinates (mist and rain), phrasal associates (pony and express), and super- +and subordinates. Each relationship contained an average of 23 word pairs. +Hodgson's results showed that priming effects were exhibited by the prime-target +pairs in all six categories. + +We use the same methodology as Pad\'{o} and Lapata \shortcite{pado07dependency} +for this data set; the prime-target (Related Primes) cosine similarity is +compared with the average cosine similarity between the prime and all other +targets (Unrelated Primes) within the semantic category. The priming effect +is the difference between the two similarity values. + +\subsection{Experiment 2} +We use six standard word space benchmarks to test our hypothesis that LPP can +accurately capture general semantic knowledge and association based relations. +The benchmarks come in two forms: word association and word choice tests. + +Word choice tests provide a target word and a list of options, one of which has +the desired relation to the target. To answer these questions, we select the +option whose representation has the highest cosine similarity with the target. +Three word choice synonymy benchmarks are used: the Test of English as a Foreign +Language (TOEFL) test set from \cite{landauer98introduction}, the English as a +Second Language (ESL) test set from \cite{turney01mining}, and the Canadian +Reader's Digest Word Power (RDWP) from \cite{jarmasz03rogets}, which unlike the +previous two tests, allows the target and options to be multi-word phrases. + +Word association tests measure the semantic relatedness of two words by +comparing their similarity in the word space with human judgements. These tests +are more precise than word choice tests because they take into account the +specific value of the word similarity. Three word association benchmarks are +used: the word similarity data set of Rubenstein and Goodenough +\shortcite{rubenstein65contextual}, the word-relatedness data set of Finkelstein +et al. \shortcite{finkelstein02placing}, and the antonymy data set of Deese +\shortcite{deese64associative}, which measures the degree to which high +similarity captures the antonymy relationship. The Finkelstein et al. test is +notable in that the specific type of relatedness is left unspecified; human test +takers were free to score based on any possible relationship between the two +words. + +\section{Results and Discussion} + +The LPP-based models show mixed performance in comparison to existing models on +normed priming tasks, shown in Table \ref{tab:semantic-priming}. Adding LPP to +the VSM decreased performance; however, when WIKI was used instead of TASA, the +VSM+LPP model increased $.15$ on all correlations, whereas LSA's performance decreased. +This suggests that LPP needs more data than LSA to properly model the word space +manifold. +% +WC+LPP performs comparably to HAL, which indicates that LPP is effective in +retaining the original WC space's structure in significantly fewer dimensions. + +For the categorical priming tests shown in Table +\ref{tab:categorical-priming-b}, LPP-based models show competitive results. +VSM+LPP with the WIKI corpus performs much better than other VSM+LPP +configurations. Unlike in the previous priming experiment, adding LPP to the +base models resulted in a significant performance improvement. +% +We also note that both HAL models and the VSM+LPP+TF-IDF model have high +similarity ratings for unrelated primes. We posit that these models' feature +weighting results in poor differentiation between words in the same semantic +category, which causes their decreased performance. + +For experiment 2, LPP-based spaces showed mixed results on word choice +benchmarks, while showing notable improvement on the more precise word +association benchmarks. Table \ref{tab:exp3} lists the results. Notably, +LPP-based spaces performed well on the ESL synonym benchmark but poorly on the +TOEFL synonym benchmark, even when the larger WIKI corpus was used. This +suggests that LPP was not effective in retaining the relationship between +certain classes of synonyms. Given that performance did not improve with the +WIKI corpus, further analysis is needed to identify whether a different +representation of the local structure would improve results or if the poor +performance is due to another factor. While LSA and VSM model performed best on +all benchmarks, LPP-based spaces performed competitively on the word association +tests. In all but two tests, the WC+LPP model outperformed HAL. + +The results from both experiments indicate that LPP is capable of accurately +representing distributional information in a much lower dimensional space. +However, in many cases applications using the SVD-reduced representations +performed better. In addition, application of standard weighting schemes +worsened performance, which suggests that the local neighborhood is adversely +distorted. + +\section{Conclusions and Future Work} + +We have shown that LPP is an effective dimensionality reduction technique for +word space algorithms. In several benchmarks, LPP provided a significant +benefit to the base models and in a few cases outperformed the SVD. However, it +does not perform consistently better than existing models. Future work will +focus on four themes: identifying optimal LPP parameter configurations; +improving LPP with weighting; measuring LPP's capacity to capture higher order +co-occurrence relationships, as was shown for the SVD \cite{lemaire06effects}; +and investigating whether more computationally expensive nonlinear reduction +algorithms such as ISOMAP \cite{tenenbaum00global} are better for word space +algorithms. We plan to release open source implementations of the LPP-based +models. + +\bibliographystyle{acl} +\bibliography{gems_lpsa} + +\end{document} diff --git a/papers/2010_semeval_hermit/acl.bst b/papers/2010_semeval_hermit/acl.bst new file mode 100644 index 00000000..b95ec040 --- /dev/null +++ b/papers/2010_semeval_hermit/acl.bst @@ -0,0 +1,1322 @@ + +% BibTeX `acl' style file for BibTeX version 0.99c, LaTeX version 2.09 +% This version was made by modifying `aaai-named' format based on the master +% file by Oren Patashnik (PATASHNIK@SCORE.STANFORD.EDU) + +% Copyright (C) 1985, all rights reserved. +% Modifications Copyright 1988, Peter F. Patel-Schneider +% Further modifictions by Stuart Shieber, 1991, and Fernando Pereira, 1992. +% Copying of this file is authorized only if either +% (1) you make absolutely no changes to your copy, including name, or +% (2) if you do make changes, you name it something other than +% btxbst.doc, plain.bst, unsrt.bst, alpha.bst, and abbrv.bst. +% This restriction helps ensure that all standard styles are identical. + +% There are undoubtably bugs in this style. If you make bug fixes, +% improvements, etc. please let me know. My e-mail address is: +% pfps@spar.slb.com + +% Citation format: [author-last-name, year] +% [author-last-name and author-last-name, year] +% [author-last-name {\em et al.}, year] +% +% Reference list ordering: alphabetical by author or whatever passes +% for author in the absence of one. +% +% This BibTeX style has support for short (year only) citations. This +% is done by having the citations actually look like +% \citename{name-info, }year +% The LaTeX style has to have the following +% \let\@internalcite\cite +% \def\cite{\def\citename##1{##1}\@internalcite} +% \def\shortcite{\def\citename##1{}\@internalcite} +% \def\@biblabel#1{\def\citename##1{##1}[#1]\hfill} +% which makes \shortcite the macro for short citations. + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% Changes made by SMS for thesis style +% no emphasis on "et al." +% "Ph.D." includes periods (not "PhD") +% moved year to immediately after author's name +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +ENTRY + { address + author + booktitle + chapter + edition + editor + howpublished + institution + journal + key + month + note + number + organization + pages + publisher + school + series + title + type + volume + year + } + {} + { label extra.label sort.label } + +INTEGERS { output.state before.all mid.sentence after.sentence after.block } + +FUNCTION {init.state.consts} +{ #0 'before.all := + #1 'mid.sentence := + #2 'after.sentence := + #3 'after.block := +} + +STRINGS { s t } + +FUNCTION {output.nonnull} +{ 's := + output.state mid.sentence = + { ", " * write$ } + { output.state after.block = + { add.period$ write$ + newline$ + "\newblock " write$ + } + { output.state before.all = + 'write$ + { add.period$ " " * write$ } + if$ + } + if$ + mid.sentence 'output.state := + } + if$ + s +} + +FUNCTION {output} +{ duplicate$ empty$ + 'pop$ + 'output.nonnull + if$ +} + +FUNCTION {output.check} +{ 't := + duplicate$ empty$ + { pop$ "empty " t * " in " * cite$ * warning$ } + 'output.nonnull + if$ +} + +FUNCTION {output.bibitem} +{ newline$ + + "\bibitem[" write$ + label write$ + "]{" write$ + + cite$ write$ + "}" write$ + newline$ + "" + before.all 'output.state := +} + +FUNCTION {fin.entry} +{ add.period$ + write$ + newline$ +} + +FUNCTION {new.block} +{ output.state before.all = + 'skip$ + { after.block 'output.state := } + if$ +} + +FUNCTION {new.sentence} +{ output.state after.block = + 'skip$ + { output.state before.all = + 'skip$ + { after.sentence 'output.state := } + if$ + } + if$ +} + +FUNCTION {not} +{ { #0 } + { #1 } + if$ +} + +FUNCTION {and} +{ 'skip$ + { pop$ #0 } + if$ +} + +FUNCTION {or} +{ { pop$ #1 } + 'skip$ + if$ +} + +FUNCTION {new.block.checka} +{ empty$ + 'skip$ + 'new.block + if$ +} + +FUNCTION {new.block.checkb} +{ empty$ + swap$ empty$ + and + 'skip$ + 'new.block + if$ +} + +FUNCTION {new.sentence.checka} +{ empty$ + 'skip$ + 'new.sentence + if$ +} + +FUNCTION {new.sentence.checkb} +{ empty$ + swap$ empty$ + and + 'skip$ + 'new.sentence + if$ +} + +FUNCTION {field.or.null} +{ duplicate$ empty$ + { pop$ "" } + 'skip$ + if$ +} + +FUNCTION {emphasize} +{ duplicate$ empty$ + { pop$ "" } + { "{\em " swap$ * "}" * } + if$ +} + +INTEGERS { nameptr namesleft numnames } + +FUNCTION {format.names} +{ 's := + #1 'nameptr := + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + + { s nameptr "{ff~}{vv~}{ll}{, jj}" format.name$ 't := + + nameptr #1 > + { namesleft #1 > + { ", " * t * } + { numnames #2 > + { "," * } + 'skip$ + if$ + t "others" = + { " et~al." * } + { " and " * t * } + if$ + } + if$ + } + 't + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {format.authors} +{ author empty$ + { "" } + { author format.names } + if$ +} + +FUNCTION {format.editors} +{ editor empty$ + { "" } + { editor format.names + editor num.names$ #1 > + { ", editors" * } + { ", editor" * } + if$ + } + if$ +} + +FUNCTION {format.title} +{ title empty$ + { "" } + + { title "t" change.case$ } + + if$ +} + +FUNCTION {n.dashify} +{ 't := + "" + { t empty$ not } + { t #1 #1 substring$ "-" = + { t #1 #2 substring$ "--" = not + { "--" * + t #2 global.max$ substring$ 't := + } + { { t #1 #1 substring$ "-" = } + { "-" * + t #2 global.max$ substring$ 't := + } + while$ + } + if$ + } + { t #1 #1 substring$ * + t #2 global.max$ substring$ 't := + } + if$ + } + while$ +} + +FUNCTION {format.date} +{ year empty$ + { month empty$ + { "" } + { "there's a month but no year in " cite$ * warning$ + month + } + if$ + } + { month empty$ + { "" } + { month } + if$ + } + if$ +} + +FUNCTION {format.btitle} +{ title emphasize +} + +FUNCTION {tie.or.space.connect} +{ duplicate$ text.length$ #3 < + { "~" } + { " " } + if$ + swap$ * * +} + +FUNCTION {either.or.check} +{ empty$ + 'pop$ + { "can't use both " swap$ * " fields in " * cite$ * warning$ } + if$ +} + +FUNCTION {format.bvolume} +{ volume empty$ + { "" } + { "volume" volume tie.or.space.connect + series empty$ + 'skip$ + { " of " * series emphasize * } + if$ + "volume and number" number either.or.check + } + if$ +} + +FUNCTION {format.number.series} +{ volume empty$ + { number empty$ + { series field.or.null } + { output.state mid.sentence = + { "number" } + { "Number" } + if$ + number tie.or.space.connect + series empty$ + { "there's a number but no series in " cite$ * warning$ } + { " in " * series * } + if$ + } + if$ + } + { "" } + if$ +} + +FUNCTION {format.edition} +{ edition empty$ + { "" } + { output.state mid.sentence = + { edition "l" change.case$ " edition" * } + { edition "t" change.case$ " edition" * } + if$ + } + if$ +} + +INTEGERS { multiresult } + +FUNCTION {multi.page.check} +{ 't := + #0 'multiresult := + { multiresult not + t empty$ not + and + } + { t #1 #1 substring$ + duplicate$ "-" = + swap$ duplicate$ "," = + swap$ "+" = + or or + { #1 'multiresult := } + { t #2 global.max$ substring$ 't := } + if$ + } + while$ + multiresult +} + +FUNCTION {format.pages} +{ pages empty$ + { "" } + { pages multi.page.check + { "pages" pages n.dashify tie.or.space.connect } + { "page" pages tie.or.space.connect } + if$ + } + if$ +} + +FUNCTION {format.year.label} +{ year extra.label * +} + +FUNCTION {format.vol.num.pages} +{ volume field.or.null + number empty$ + 'skip$ + { "(" number * ")" * * + volume empty$ + { "there's a number but no volume in " cite$ * warning$ } + 'skip$ + if$ + } + if$ + pages empty$ + 'skip$ + { duplicate$ empty$ + { pop$ format.pages } + { ":" * pages n.dashify * } + if$ + } + if$ +} + +FUNCTION {format.chapter.pages} +{ chapter empty$ + 'format.pages + { type empty$ + { "chapter" } + { type "l" change.case$ } + if$ + chapter tie.or.space.connect + pages empty$ + 'skip$ + { ", " * format.pages * } + if$ + } + if$ +} + +FUNCTION {format.in.ed.booktitle} +{ booktitle empty$ + { "" } + { editor empty$ + { "In " booktitle emphasize * } + { "In " format.editors * ", " * booktitle emphasize * } + if$ + } + if$ +} + +FUNCTION {empty.misc.check} +{ author empty$ title empty$ howpublished empty$ + month empty$ year empty$ note empty$ + and and and and and + + key empty$ not and + + { "all relevant fields are empty in " cite$ * warning$ } + 'skip$ + if$ +} + +FUNCTION {format.thesis.type} +{ type empty$ + 'skip$ + { pop$ + type "t" change.case$ + } + if$ +} + +FUNCTION {format.tr.number} +{ type empty$ + { "Technical Report" } + 'type + if$ + number empty$ + { "t" change.case$ } + { number tie.or.space.connect } + if$ +} + +FUNCTION {format.article.crossref} +{ key empty$ + { journal empty$ + { "need key or journal for " cite$ * " to crossref " * crossref * + warning$ + "" + } + { "In {\em " journal * "\/}" * } + if$ + } + { "In " key * } + if$ + " \cite{" * crossref * "}" * +} + +FUNCTION {format.crossref.editor} +{ editor #1 "{vv~}{ll}" format.name$ + editor num.names$ duplicate$ + #2 > + { pop$ " et~al." * } + { #2 < + 'skip$ + { editor #2 "{ff }{vv }{ll}{ jj}" format.name$ "others" = + { " et~al." * } + { " and " * editor #2 "{vv~}{ll}" format.name$ * } + if$ + } + if$ + } + if$ +} + +FUNCTION {format.book.crossref} +{ volume empty$ + { "empty volume in " cite$ * "'s crossref of " * crossref * warning$ + "In " + } + { "Volume" volume tie.or.space.connect + " of " * + } + if$ + editor empty$ + editor field.or.null author field.or.null = + or + { key empty$ + { series empty$ + { "need editor, key, or series for " cite$ * " to crossref " * + crossref * warning$ + "" * + } + { "{\em " * series * "\/}" * } + if$ + } + { key * } + if$ + } + { format.crossref.editor * } + if$ + " \cite{" * crossref * "}" * +} + +FUNCTION {format.incoll.inproc.crossref} +{ editor empty$ + editor field.or.null author field.or.null = + or + { key empty$ + { booktitle empty$ + { "need editor, key, or booktitle for " cite$ * " to crossref " * + crossref * warning$ + "" + } + { "In {\em " booktitle * "\/}" * } + if$ + } + { "In " key * } + if$ + } + { "In " format.crossref.editor * } + if$ + " \cite{" * crossref * "}" * +} + +FUNCTION {article} +{ output.bibitem + format.authors "author" output.check + new.block + format.year.label "year" output.check + new.block + format.title "title" output.check + new.block + crossref missing$ + { journal emphasize "journal" output.check + format.vol.num.pages output + format.date output + } + { format.article.crossref output.nonnull + format.pages output + } + if$ + new.block + note output + fin.entry +} + +FUNCTION {book} +{ output.bibitem + author empty$ + { format.editors "author and editor" output.check } + { format.authors output.nonnull + crossref missing$ + { "author and editor" editor either.or.check } + 'skip$ + if$ + } + if$ + new.block + format.year.label "year" output.check + new.block + format.btitle "title" output.check + crossref missing$ + { format.bvolume output + new.block + format.number.series output + new.sentence + publisher "publisher" output.check + address output + } + { new.block + format.book.crossref output.nonnull + } + if$ + format.edition output + format.date output + new.block + note output + fin.entry +} + +FUNCTION {booklet} +{ output.bibitem + format.authors output + new.block + format.year.label "year" output.check + new.block + format.title "title" output.check + howpublished address new.block.checkb + howpublished output + address output + format.date output + new.block + note output + fin.entry +} + +FUNCTION {inbook} +{ output.bibitem + author empty$ + { format.editors "author and editor" output.check } + { format.authors output.nonnull + crossref missing$ + { "author and editor" editor either.or.check } + 'skip$ + if$ + } + if$ + format.year.label "year" output.check + new.block + new.block + format.btitle "title" output.check + crossref missing$ + { format.bvolume output + format.chapter.pages "chapter and pages" output.check + new.block + format.number.series output + new.sentence + publisher "publisher" output.check + address output + } + { format.chapter.pages "chapter and pages" output.check + new.block + format.book.crossref output.nonnull + } + if$ + format.edition output + format.date output + new.block + note output + fin.entry +} + +FUNCTION {incollection} +{ output.bibitem + format.authors "author" output.check + new.block + format.year.label "year" output.check + new.block + format.title "title" output.check + new.block + crossref missing$ + { format.in.ed.booktitle "booktitle" output.check + format.bvolume output + format.number.series output + format.chapter.pages output + new.sentence + publisher "publisher" output.check + address output + format.edition output + format.date output + } + { format.incoll.inproc.crossref output.nonnull + format.chapter.pages output + } + if$ + new.block + note output + fin.entry +} + +FUNCTION {inproceedings} +{ output.bibitem + format.authors "author" output.check + new.block + format.year.label "year" output.check + new.block + format.title "title" output.check + new.block + crossref missing$ + { format.in.ed.booktitle "booktitle" output.check + format.bvolume output + format.number.series output + format.pages output + address empty$ + { organization publisher new.sentence.checkb + organization output + publisher output + format.date output + } + { address output.nonnull + format.date output + new.sentence + organization output + publisher output + } + if$ + } + { format.incoll.inproc.crossref output.nonnull + format.pages output + } + if$ + new.block + note output + fin.entry +} + +FUNCTION {conference} { inproceedings } + +FUNCTION {manual} +{ output.bibitem + author empty$ + { organization empty$ + 'skip$ + { organization output.nonnull + address output + } + if$ + } + { format.authors output.nonnull } + if$ + format.year.label "year" output.check + new.block + new.block + format.btitle "title" output.check + author empty$ + { organization empty$ + { address new.block.checka + address output + } + 'skip$ + if$ + } + { organization address new.block.checkb + organization output + address output + } + if$ + format.edition output + format.date output + new.block + note output + fin.entry +} + +FUNCTION {mastersthesis} +{ output.bibitem + format.authors "author" output.check + new.block + format.year.label "year" output.check + new.block + format.title "title" output.check + new.block + "Master's thesis" format.thesis.type output.nonnull + school "school" output.check + address output + format.date output + new.block + note output + fin.entry +} + +FUNCTION {misc} +{ output.bibitem + format.authors output + new.block + format.year.label output + new.block + title howpublished new.block.checkb + format.title output + howpublished new.block.checka + howpublished output + format.date output + new.block + note output + fin.entry + empty.misc.check +} + +FUNCTION {phdthesis} +{ output.bibitem + format.authors "author" output.check + new.block + format.year.label "year" output.check + new.block + format.btitle "title" output.check + new.block + "{Ph.D.} thesis" format.thesis.type output.nonnull + school "school" output.check + address output + format.date output + new.block + note output + fin.entry +} + +FUNCTION {proceedings} +{ output.bibitem + editor empty$ + { organization output } + { format.editors output.nonnull } + if$ + new.block + format.year.label "year" output.check + new.block + format.btitle "title" output.check + format.bvolume output + format.number.series output + address empty$ + { editor empty$ + { publisher new.sentence.checka } + { organization publisher new.sentence.checkb + organization output + } + if$ + publisher output + format.date output + } + { address output.nonnull + format.date output + new.sentence + editor empty$ + 'skip$ + { organization output } + if$ + publisher output + } + if$ + new.block + note output + fin.entry +} + +FUNCTION {techreport} +{ output.bibitem + format.authors "author" output.check + new.block + format.year.label "year" output.check + new.block + format.title "title" output.check + new.block + format.tr.number output.nonnull + institution "institution" output.check + address output + format.date output + new.block + note output + fin.entry +} + +FUNCTION {unpublished} +{ output.bibitem + format.authors "author" output.check + new.block + format.year.label "year" output.check + new.block + format.title "title" output.check + new.block + note "note" output.check + format.date output + fin.entry +} + +FUNCTION {default.type} { misc } + +MACRO {jan} {"January"} + +MACRO {feb} {"February"} + +MACRO {mar} {"March"} + +MACRO {apr} {"April"} + +MACRO {may} {"May"} + +MACRO {jun} {"June"} + +MACRO {jul} {"July"} + +MACRO {aug} {"August"} + +MACRO {sep} {"September"} + +MACRO {oct} {"October"} + +MACRO {nov} {"November"} + +MACRO {dec} {"December"} + +MACRO {acmcs} {"ACM Computing Surveys"} + +MACRO {acta} {"Acta Informatica"} + +MACRO {cacm} {"Communications of the ACM"} + +MACRO {ibmjrd} {"IBM Journal of Research and Development"} + +MACRO {ibmsj} {"IBM Systems Journal"} + +MACRO {ieeese} {"IEEE Transactions on Software Engineering"} + +MACRO {ieeetc} {"IEEE Transactions on Computers"} + +MACRO {ieeetcad} + {"IEEE Transactions on Computer-Aided Design of Integrated Circuits"} + +MACRO {ipl} {"Information Processing Letters"} + +MACRO {jacm} {"Journal of the ACM"} + +MACRO {jcss} {"Journal of Computer and System Sciences"} + +MACRO {scp} {"Science of Computer Programming"} + +MACRO {sicomp} {"SIAM Journal on Computing"} + +MACRO {tocs} {"ACM Transactions on Computer Systems"} + +MACRO {tods} {"ACM Transactions on Database Systems"} + +MACRO {tog} {"ACM Transactions on Graphics"} + +MACRO {toms} {"ACM Transactions on Mathematical Software"} + +MACRO {toois} {"ACM Transactions on Office Information Systems"} + +MACRO {toplas} {"ACM Transactions on Programming Languages and Systems"} + +MACRO {tcs} {"Theoretical Computer Science"} + +READ + +FUNCTION {sortify} +{ purify$ + "l" change.case$ +} + +INTEGERS { len } + +FUNCTION {chop.word} +{ 's := + 'len := + s #1 len substring$ = + { s len #1 + global.max$ substring$ } + 's + if$ +} + +INTEGERS { et.al.char.used } + +FUNCTION {initialize.et.al.char.used} +{ #0 'et.al.char.used := +} + +EXECUTE {initialize.et.al.char.used} + +FUNCTION {format.lab.names} +{ 's := + s num.names$ 'numnames := + + numnames #1 = + { s #1 "{vv }{ll}" format.name$ } + { numnames #2 = + { s #1 "{vv }{ll }and " format.name$ s #2 "{vv }{ll}" format.name$ * + } + { s #1 "{vv }{ll }\bgroup et al.\egroup " format.name$ } + if$ + } + if$ + +} + +FUNCTION {author.key.label} +{ author empty$ + { key empty$ + + { cite$ #1 #3 substring$ } + + { key #3 text.prefix$ } + if$ + } + { author format.lab.names } + if$ +} + +FUNCTION {author.editor.key.label} +{ author empty$ + { editor empty$ + { key empty$ + + { cite$ #1 #3 substring$ } + + { key #3 text.prefix$ } + if$ + } + { editor format.lab.names } + if$ + } + { author format.lab.names } + if$ +} + +FUNCTION {author.key.organization.label} +{ author empty$ + { key empty$ + { organization empty$ + + { cite$ #1 #3 substring$ } + + { "The " #4 organization chop.word #3 text.prefix$ } + if$ + } + { key #3 text.prefix$ } + if$ + } + { author format.lab.names } + if$ +} + +FUNCTION {editor.key.organization.label} +{ editor empty$ + { key empty$ + { organization empty$ + + { cite$ #1 #3 substring$ } + + { "The " #4 organization chop.word #3 text.prefix$ } + if$ + } + { key #3 text.prefix$ } + if$ + } + { editor format.lab.names } + if$ +} + +FUNCTION {calc.label} +{ type$ "book" = + type$ "inbook" = + or + 'author.editor.key.label + { type$ "proceedings" = + 'editor.key.organization.label + { type$ "manual" = + 'author.key.organization.label + 'author.key.label + if$ + } + if$ + } + if$ + duplicate$ + + "\protect\citename{" swap$ * "}" * + year field.or.null purify$ * + 'label := + year field.or.null purify$ * + + sortify 'sort.label := +} + +FUNCTION {sort.format.names} +{ 's := + #1 'nameptr := + "" + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + { nameptr #1 > + { " " * } + 'skip$ + if$ + + s nameptr "{vv{ } }{ll{ }}{ ff{ }}{ jj{ }}" format.name$ 't := + + nameptr numnames = t "others" = and + { "et al" * } + { t sortify * } + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {sort.format.title} +{ 't := + "A " #2 + "An " #3 + "The " #4 t chop.word + chop.word + chop.word + sortify + #1 global.max$ substring$ +} + +FUNCTION {author.sort} +{ author empty$ + { key empty$ + { "to sort, need author or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { author sort.format.names } + if$ +} + +FUNCTION {author.editor.sort} +{ author empty$ + { editor empty$ + { key empty$ + { "to sort, need author, editor, or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { editor sort.format.names } + if$ + } + { author sort.format.names } + if$ +} + +FUNCTION {author.organization.sort} +{ author empty$ + { organization empty$ + { key empty$ + { "to sort, need author, organization, or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { "The " #4 organization chop.word sortify } + if$ + } + { author sort.format.names } + if$ +} + +FUNCTION {editor.organization.sort} +{ editor empty$ + { organization empty$ + { key empty$ + { "to sort, need editor, organization, or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { "The " #4 organization chop.word sortify } + if$ + } + { editor sort.format.names } + if$ +} + +FUNCTION {presort} + +{ calc.label + sort.label + " " + * + type$ "book" = + + type$ "inbook" = + or + 'author.editor.sort + { type$ "proceedings" = + 'editor.organization.sort + { type$ "manual" = + 'author.organization.sort + 'author.sort + if$ + } + if$ + } + if$ + + * + + " " + * + year field.or.null sortify + * + " " + * + title field.or.null + sort.format.title + * + #1 entry.max$ substring$ + 'sort.key$ := +} + +ITERATE {presort} + +SORT + +STRINGS { longest.label last.sort.label next.extra } + +INTEGERS { longest.label.width last.extra.num } + +FUNCTION {initialize.longest.label} +{ "" 'longest.label := + #0 int.to.chr$ 'last.sort.label := + "" 'next.extra := + #0 'longest.label.width := + #0 'last.extra.num := +} + +FUNCTION {forward.pass} +{ last.sort.label sort.label = + { last.extra.num #1 + 'last.extra.num := + last.extra.num int.to.chr$ 'extra.label := + } + { "a" chr.to.int$ 'last.extra.num := + "" 'extra.label := + sort.label 'last.sort.label := + } + if$ +} + +FUNCTION {reverse.pass} +{ next.extra "b" = + { "a" 'extra.label := } + 'skip$ + if$ + label extra.label * 'label := + label width$ longest.label.width > + { label 'longest.label := + label width$ 'longest.label.width := + } + 'skip$ + if$ + extra.label 'next.extra := +} + +EXECUTE {initialize.longest.label} + +ITERATE {forward.pass} + +REVERSE {reverse.pass} + +FUNCTION {begin.bib} + +{ et.al.char.used + { "\newcommand{\etalchar}[1]{$^{#1}$}" write$ newline$ } + 'skip$ + if$ + preamble$ empty$ + + 'skip$ + { preamble$ write$ newline$ } + if$ + + "\begin{thebibliography}{" "}" * write$ newline$ + +} + +EXECUTE {begin.bib} + +EXECUTE {init.state.consts} + +ITERATE {call.type$} + +FUNCTION {end.bib} +{ newline$ + "\end{thebibliography}" write$ newline$ +} + +EXECUTE {end.bib} + diff --git a/papers/2010_semeval_hermit/acl2010.pdf b/papers/2010_semeval_hermit/acl2010.pdf new file mode 100644 index 00000000..4966a7e7 Binary files /dev/null and b/papers/2010_semeval_hermit/acl2010.pdf differ diff --git a/papers/2010_semeval_hermit/acl2010.sty b/papers/2010_semeval_hermit/acl2010.sty new file mode 100644 index 00000000..e580ae8e --- /dev/null +++ b/papers/2010_semeval_hermit/acl2010.sty @@ -0,0 +1,370 @@ +% File acl2010.sty +% same as -- +% File acl-ijcnlp2009.sty +% same as -- +% File eacl2006.sty +% September 19, 2005 +% Contact: e.agirre@ehu.es or Sergi.Balari@uab.es + +% This is the LaTeX style file for EACL 2006. It is nearly identical to the +% style files for ACL2005, ACL 2002, ACL 2001, ACL 2000, EACL 95 and EACL +% 99. +% +% Changes made include: adapt layout to A4 and centimeters, widden abstract + +% This is the LaTeX style file for ACL 2000. It is nearly identical to the +% style files for EACL 95 and EACL 99. Minor changes include editing the +% instructions to reflect use of \documentclass rather than \documentstyle +% and removing the white space before the title on the first page +% -- John Chen, June 29, 2000 + +% To convert from submissions prepared using the style file aclsub.sty +% prepared for the ACL 2000 conference, proceed as follows: +% 1) Remove submission-specific information: \whichsession, \id, +% \wordcount, \otherconferences, \area, \keywords +% 2) \summary should be removed. The summary material should come +% after \maketitle and should be in the ``abstract'' environment +% 3) Check all citations. This style should handle citations correctly +% and also allows multiple citations separated by semicolons. +% 4) Check figures and examples. Because the final format is double- +% column, some adjustments may have to be made to fit text in the column +% or to choose full-width (\figure*} figures. +% 5) Change the style reference from aclsub to acl2000, and be sure +% this style file is in your TeX search path + + +% This is the LaTeX style file for EACL-95. It is identical to the +% style file for ANLP '94 except that the margins are adjusted for A4 +% paper. -- abney 13 Dec 94 + +% The ANLP '94 style file is a slightly modified +% version of the style used for AAAI and IJCAI, using some changes +% prepared by Fernando Pereira and others and some minor changes +% by Paul Jacobs. + +% Papers prepared using the aclsub.sty file and acl.bst bibtex style +% should be easily converted to final format using this style. +% (1) Submission information (\wordcount, \subject, and \makeidpage) +% should be removed. +% (2) \summary should be removed. The summary material should come +% after \maketitle and should be in the ``abstract'' environment +% (between \begin{abstract} and \end{abstract}). +% (3) Check all citations. This style should handle citations correctly +% and also allows multiple citations separated by semicolons. +% (4) Check figures and examples. Because the final format is double- +% column, some adjustments may have to be made to fit text in the column +% or to choose full-width (\figure*} figures. + +% Place this in a file called aclap.sty in the TeX search path. +% (Placing it in the same directory as the paper should also work.) + +% Prepared by Peter F. Patel-Schneider, liberally using the ideas of +% other style hackers, including Barbara Beeton. +% This style is NOT guaranteed to work. It is provided in the hope +% that it will make the preparation of papers easier. +% +% There are undoubtably bugs in this style. If you make bug fixes, +% improvements, etc. please let me know. My e-mail address is: +% pfps@research.att.com + +% Papers are to be prepared using the ``acl'' bibliography style, +% as follows: +% \documentclass[11pt]{article} +% \usepackage{acl2000} +% \title{Title} +% \author{Author 1 \and Author 2 \\ Address line \\ Address line \And +% Author 3 \\ Address line \\ Address line} +% \begin{document} +% ... +% \bibliography{bibliography-file} +% \bibliographystyle{acl} +% \end{document} + +% Author information can be set in various styles: +% For several authors from the same institution: +% \author{Author 1 \and ... \and Author n \\ +% Address line \\ ... \\ Address line} +% if the names do not fit well on one line use +% Author 1 \\ {\bf Author 2} \\ ... \\ {\bf Author n} \\ +% For authors from different institutions: +% \author{Author 1 \\ Address line \\ ... \\ Address line +% \And ... \And +% Author n \\ Address line \\ ... \\ Address line} +% To start a seperate ``row'' of authors use \AND, as in +% \author{Author 1 \\ Address line \\ ... \\ Address line +% \AND +% Author 2 \\ Address line \\ ... \\ Address line \And +% Author 3 \\ Address line \\ ... \\ Address line} + +% If the title and author information does not fit in the area allocated, +% place \setlength\titlebox{} right after +% \usepackage{acl2000} +% where can be something larger than 2.25in + +% \typeout{Conference Style for ACL 2000 -- released June 20, 2000} +\typeout{Conference Style for ACL 2005 -- released Octobe 11, 2004} + +% NOTE: Some laser printers have a serious problem printing TeX output. +% These printing devices, commonly known as ``write-white'' laser +% printers, tend to make characters too light. To get around this +% problem, a darker set of fonts must be created for these devices. +% + +%% % Physical page layout - slightly modified from IJCAI by pj +%% \setlength\topmargin{0.0in} \setlength\oddsidemargin{-0.0in} +%% \setlength\textheight{9.0in} \setlength\textwidth{6.5in} +%% \setlength\columnsep{0.2in} +%% \newlength\titlebox +%% \setlength\titlebox{2.25in} +%% \setlength\headheight{0pt} \setlength\headsep{0pt} +%% %\setlength\footheight{0pt} +%% \setlength\footskip{0pt} +%% \thispagestyle{empty} \pagestyle{empty} +%% \flushbottom \twocolumn \sloppy + +%% Original A4 version of page layout +%% \setlength\topmargin{-0.45cm} % changed by Rz -1.4 +%% \setlength\oddsidemargin{.8mm} % was -0cm, changed by Rz +%% \setlength\textheight{23.5cm} +%% \setlength\textwidth{15.8cm} +%% \setlength\columnsep{0.6cm} +%% \newlength\titlebox +%% \setlength\titlebox{2.00in} +%% \setlength\headheight{5pt} +%% \setlength\headsep{0pt} +%% \setlength\footheight{0pt} +%% \setlength\footskip{0pt} +%% \thispagestyle{empty} +%% \pagestyle{empty} + +% A4 modified by Eneko +\setlength{\paperwidth}{21cm} % A4 +\setlength{\paperheight}{29.7cm}% A4 +\setlength\topmargin{-0.5cm} +\setlength\oddsidemargin{0cm} +\setlength\textheight{24.7cm} +\setlength\textwidth{16.0cm} +\setlength\columnsep{0.6cm} +\newlength\titlebox +\setlength\titlebox{2.00in} +\setlength\headheight{5pt} +\setlength\headsep{0pt} +\thispagestyle{empty} +\pagestyle{empty} + + +\flushbottom \twocolumn \sloppy + +% We're never going to need a table of contents, so just flush it to +% save space --- suggested by drstrip@sandia-2 +\def\addcontentsline#1#2#3{} + +% Title stuff, taken from deproc. +\def\maketitle{\par + \begingroup + \def\thefootnote{\fnsymbol{footnote}} + \def\@makefnmark{\hbox to 0pt{$^{\@thefnmark}$\hss}} + \twocolumn[\@maketitle] \@thanks + \endgroup + \setcounter{footnote}{0} + \let\maketitle\relax \let\@maketitle\relax + \gdef\@thanks{}\gdef\@author{}\gdef\@title{}\let\thanks\relax} +\def\@maketitle{\vbox to \titlebox{\hsize\textwidth + \linewidth\hsize \vskip 0.125in minus 0.125in \centering + {\Large\bf \@title \par} \vskip 0.2in plus 1fil minus 0.1in + {\def\and{\unskip\enspace{\rm and}\enspace}% + \def\And{\end{tabular}\hss \egroup \hskip 1in plus 2fil + \hbox to 0pt\bgroup\hss \begin{tabular}[t]{c}\bf}% + \def\AND{\end{tabular}\hss\egroup \hfil\hfil\egroup + \vskip 0.25in plus 1fil minus 0.125in + \hbox to \linewidth\bgroup\large \hfil\hfil + \hbox to 0pt\bgroup\hss \begin{tabular}[t]{c}\bf} + \hbox to \linewidth\bgroup\large \hfil\hfil + \hbox to 0pt\bgroup\hss \begin{tabular}[t]{c}\bf\@author + \end{tabular}\hss\egroup + \hfil\hfil\egroup} + \vskip 0.3in plus 2fil minus 0.1in +}} + +% margins for abstract +\renewenvironment{abstract}% + {\centerline{\large\bf Abstract}% + \begin{list}{}% + {\setlength{\rightmargin}{0.6cm}% + \setlength{\leftmargin}{0.6cm}}% + \item[]\ignorespaces}% + {\unskip\end{list}} + +%\renewenvironment{abstract}{\centerline{\large\bf +% Abstract}\vspace{0.5ex}\begin{quote}}{\par\end{quote}\vskip 1ex} + + +% bibliography + +\def\thebibliography#1{\section*{References} + \global\def\@listi{\leftmargin\leftmargini + \labelwidth\leftmargini \advance\labelwidth-\labelsep + \topsep 1pt plus 2pt minus 1pt + \parsep 0.25ex plus 1pt \itemsep 0.25ex plus 1pt} + \list {[\arabic{enumi}]}{\settowidth\labelwidth{[#1]}\leftmargin\labelwidth + \advance\leftmargin\labelsep\usecounter{enumi}} + \def\newblock{\hskip .11em plus .33em minus -.07em} + \sloppy + \sfcode`\.=1000\relax} + +\def\@up#1{\raise.2ex\hbox{#1}} + +% most of cite format is from aclsub.sty by SMS + +% don't box citations, separate with ; and a space +% also, make the penalty between citations negative: a good place to break +% changed comma back to semicolon pj 2/1/90 +% \def\@citex[#1]#2{\if@filesw\immediate\write\@auxout{\string\citation{#2}}\fi +% \def\@citea{}\@cite{\@for\@citeb:=#2\do +% {\@citea\def\@citea{;\penalty\@citeseppen\ }\@ifundefined +% {b@\@citeb}{{\bf ?}\@warning +% {Citation `\@citeb' on page \thepage \space undefined}}% +% {\csname b@\@citeb\endcsname}}}{#1}} + +% don't box citations, separate with ; and a space +% Replaced for multiple citations (pj) +% don't box citations and also add space, semicolon between multiple citations +\def\@citex[#1]#2{\if@filesw\immediate\write\@auxout{\string\citation{#2}}\fi + \def\@citea{}\@cite{\@for\@citeb:=#2\do + {\@citea\def\@citea{; }\@ifundefined + {b@\@citeb}{{\bf ?}\@warning + {Citation `\@citeb' on page \thepage \space undefined}}% + {\csname b@\@citeb\endcsname}}}{#1}} + +% Allow short (name-less) citations, when used in +% conjunction with a bibliography style that creates labels like +% \citename{, } +% +\let\@internalcite\cite +\def\cite{\def\citename##1{##1, }\@internalcite} +\def\shortcite{\def\citename##1{}\@internalcite} +\def\newcite{\def\citename##1{{\frenchspacing##1} (}\@internalciteb} + +% Macros for \newcite, which leaves name in running text, and is +% otherwise like \shortcite. +\def\@citexb[#1]#2{\if@filesw\immediate\write\@auxout{\string\citation{#2}}\fi + \def\@citea{}\@newcite{\@for\@citeb:=#2\do + {\@citea\def\@citea{;\penalty\@m\ }\@ifundefined + {b@\@citeb}{{\bf ?}\@warning + {Citation `\@citeb' on page \thepage \space undefined}}% +{\csname b@\@citeb\endcsname}}}{#1}} +\def\@internalciteb{\@ifnextchar [{\@tempswatrue\@citexb}{\@tempswafalse\@citexb[]}} + +\def\@newcite#1#2{{#1\if@tempswa, #2\fi)}} + +\def\@biblabel#1{\def\citename##1{##1}[#1]\hfill} + +%%% More changes made by SMS (originals in latex.tex) +% Use parentheses instead of square brackets in the text. +\def\@cite#1#2{({#1\if@tempswa , #2\fi})} + +% Don't put a label in the bibliography at all. Just use the unlabeled format +% instead. +\def\thebibliography#1{\vskip\parskip% +\vskip\baselineskip% +\def\baselinestretch{1}% +\ifx\@currsize\normalsize\@normalsize\else\@currsize\fi% +\vskip-\parskip% +\vskip-\baselineskip% +\section*{References\@mkboth + {References}{References}}\list + {}{\setlength{\labelwidth}{0pt}\setlength{\leftmargin}{\parindent} + \setlength{\itemindent}{-\parindent}} + \def\newblock{\hskip .11em plus .33em minus -.07em} + \sloppy\clubpenalty4000\widowpenalty4000 + \sfcode`\.=1000\relax} +\let\endthebibliography=\endlist + +% Allow for a bibliography of sources of attested examples +\def\thesourcebibliography#1{\vskip\parskip% +\vskip\baselineskip% +\def\baselinestretch{1}% +\ifx\@currsize\normalsize\@normalsize\else\@currsize\fi% +\vskip-\parskip% +\vskip-\baselineskip% +\section*{Sources of Attested Examples\@mkboth + {Sources of Attested Examples}{Sources of Attested Examples}}\list + {}{\setlength{\labelwidth}{0pt}\setlength{\leftmargin}{\parindent} + \setlength{\itemindent}{-\parindent}} + \def\newblock{\hskip .11em plus .33em minus -.07em} + \sloppy\clubpenalty4000\widowpenalty4000 + \sfcode`\.=1000\relax} +\let\endthesourcebibliography=\endlist + +\def\@lbibitem[#1]#2{\item[]\if@filesw + { \def\protect##1{\string ##1\space}\immediate + \write\@auxout{\string\bibcite{#2}{#1}}\fi\ignorespaces}} + +\def\@bibitem#1{\item\if@filesw \immediate\write\@auxout + {\string\bibcite{#1}{\the\c@enumi}}\fi\ignorespaces} + +% sections with less space +\def\section{\@startsection {section}{1}{\z@}{-2.0ex plus + -0.5ex minus -.2ex}{1.5ex plus 0.3ex minus .2ex}{\large\bf\raggedright}} +\def\subsection{\@startsection{subsection}{2}{\z@}{-1.8ex plus + -0.5ex minus -.2ex}{0.8ex plus .2ex}{\normalsize\bf\raggedright}} +%% changed by KO to - values to get teh initial parindent right +\def\subsubsection{\@startsection{subsubsection}{3}{\z@}{-1.5ex plus + -0.5ex minus -.2ex}{0.5ex plus .2ex}{\normalsize\bf\raggedright}} +\def\paragraph{\@startsection{paragraph}{4}{\z@}{1.5ex plus + 0.5ex minus .2ex}{-1em}{\normalsize\bf}} +\def\subparagraph{\@startsection{subparagraph}{5}{\parindent}{1.5ex plus + 0.5ex minus .2ex}{-1em}{\normalsize\bf}} + +% Footnotes +\footnotesep 6.65pt % +\skip\footins 9pt plus 4pt minus 2pt +\def\footnoterule{\kern-3pt \hrule width 5pc \kern 2.6pt } +\setcounter{footnote}{0} + +% Lists and paragraphs +\parindent 1em +\topsep 4pt plus 1pt minus 2pt +\partopsep 1pt plus 0.5pt minus 0.5pt +\itemsep 2pt plus 1pt minus 0.5pt +\parsep 2pt plus 1pt minus 0.5pt + +\leftmargin 2em \leftmargini\leftmargin \leftmarginii 2em +\leftmarginiii 1.5em \leftmarginiv 1.0em \leftmarginv .5em \leftmarginvi .5em +\labelwidth\leftmargini\advance\labelwidth-\labelsep \labelsep 5pt + +\def\@listi{\leftmargin\leftmargini} +\def\@listii{\leftmargin\leftmarginii + \labelwidth\leftmarginii\advance\labelwidth-\labelsep + \topsep 2pt plus 1pt minus 0.5pt + \parsep 1pt plus 0.5pt minus 0.5pt + \itemsep \parsep} +\def\@listiii{\leftmargin\leftmarginiii + \labelwidth\leftmarginiii\advance\labelwidth-\labelsep + \topsep 1pt plus 0.5pt minus 0.5pt + \parsep \z@ \partopsep 0.5pt plus 0pt minus 0.5pt + \itemsep \topsep} +\def\@listiv{\leftmargin\leftmarginiv + \labelwidth\leftmarginiv\advance\labelwidth-\labelsep} +\def\@listv{\leftmargin\leftmarginv + \labelwidth\leftmarginv\advance\labelwidth-\labelsep} +\def\@listvi{\leftmargin\leftmarginvi + \labelwidth\leftmarginvi\advance\labelwidth-\labelsep} + +\abovedisplayskip 7pt plus2pt minus5pt% +\belowdisplayskip \abovedisplayskip +\abovedisplayshortskip 0pt plus3pt% +\belowdisplayshortskip 4pt plus3pt minus3pt% + +% Less leading in most fonts (due to the narrow columns) +% The choices were between 1-pt and 1.5-pt leading +\def\@normalsize{\@setsize\normalsize{11pt}\xpt\@xpt} +\def\small{\@setsize\small{10pt}\ixpt\@ixpt} +\def\footnotesize{\@setsize\footnotesize{10pt}\ixpt\@ixpt} +\def\scriptsize{\@setsize\scriptsize{8pt}\viipt\@viipt} +\def\tiny{\@setsize\tiny{7pt}\vipt\@vipt} +\def\large{\@setsize\large{14pt}\xiipt\@xiipt} +\def\Large{\@setsize\Large{16pt}\xivpt\@xivpt} +\def\LARGE{\@setsize\LARGE{20pt}\xviipt\@xviipt} +\def\huge{\@setsize\huge{23pt}\xxpt\@xxpt} +\def\Huge{\@setsize\Huge{28pt}\xxvpt\@xxvpt} diff --git a/papers/2010_semeval_hermit/acl2010.tex b/papers/2010_semeval_hermit/acl2010.tex new file mode 100644 index 00000000..6377279e --- /dev/null +++ b/papers/2010_semeval_hermit/acl2010.tex @@ -0,0 +1,390 @@ +% +% File acl2010.tex +% +% Contact jshin@csie.ncnu.edu.tw or pkoehn@inf.ed.ac.uk +%% +%% Based on the style files for ACL-IJCNLP-2009, which were, in turn, +%% based on the style files for EACL-2009 and IJCNLP-2008... + +%% Based on the style files for EACL 2006 by +%%e.agirre@ehu.es or Sergi.Balari@uab.es +%% and that of ACL 08 by Joakim Nivre and Noah Smith + +\documentclass[11pt]{article} +\usepackage{acl2010} +\usepackage{times} +\usepackage{url} +\usepackage{latexsym} +%\setlength\titlebox{6.5cm} % You can expand the title box if you +% really have to + +\title{Instructions for ACL-2010 Proceedings} + +\author{Jing-Shin Chang\\ + National Chi Nan University\\ + Puli, Nantou, Taiwan, ROC.\\ + {\tt jshin@csie.ncnu.edu.tw} \And + Philipp Koehn\\ + University of Edinburgh\\ + Edinburgh, United Kingdom\\ + {\tt pkoehn@inf.ed.ac.uk}} + +\date{} + +\begin{document} +\maketitle +\begin{abstract} + This document contains the instructions for preparing a camera-ready + manuscript for the proceedings of ACL-2010. The document itself + conforms to its own specifications, and is therefore an example of + what your manuscript should look like. These instructions should be used for both + papers submitted for review and for final versions of accepted + papers. Authors are asked to conform + to all the directions reported in this document. +\end{abstract} + +\section{Credits} + +This document has been adapted from the instructions for ACL-IJCNLP-2009 +proceedings, by Jing-Shin Chang and Regina Barzilay. +Instructions for those proceedings were in turn +based on the formats of earlier ACL and EACL Conference +proceedings. Those versions were written by several persons, including +John Chen, Henry S. Thompson and Donald Walker. + +\section{Introduction} + +The following instructions are directed to authors of papers submitted +to ACL-2010 or accepted +for publication in its proceedings. All authors are required +to adhere to these specifications. Authors are required to provide a +Portable Document Format (PDF) +% das: removed reference to PostScript +% and PostScript +version of their papers. \textbf{The proceedings will be printed on A4 + paper}. Authors from countries in which access to word-processing +systems is limited should contact the publication chairs Jing-Shin Chang +(\texttt{jshin@csie.ncnu.edu.tw}) and Philipp Koehn +(\texttt{pkoehn@inf.ed.ac.uk}) as soon as possible. + +\section{General Instructions} + +Manuscripts must be in two-column format. Exceptions to the +two-column format include the title, authors' names and complete +addresses, which must be centered at the top of the first page, and +any full-width figures or tables (see the guidelines in +Subsection~\ref{ssec:first}). {\bf Type single-spaced.} Start all +pages directly under the top margin. See the guidelines later +regarding formatting the first page. The manuscript should be +printed single-sided and its length +should not exceed the maximum page limit described in Section~\ref{sec:length}. + +\subsection{Electronically-available resources} + +ACL-2010 provides this description in \LaTeX2e (acl2010.tex) and PDF +format (acl2010.pdf), along with the \LaTeX2e style file used to +format it (acl2010.sty) and an ACL bibliography style +(acl.bst). These files are all available at +\url{http://nlp.csie.ncnu.edu.tw/~shin/acl2010/publication/doc/stylefiles/}. A Microsoft Word +template file (acl2010.dot) is also available at the same URL. We +strongly recommend the use of these style files, which have been +appropriately tailored for the ACL-2010 proceedings. If you have an +option, we recommend that you use the \LaTeX2e version. \textbf{If you will be +using the Microsoft Word template, we suggest that you anonymize your +source file so that the pdf produced does not retain your identity.} +This can be done by removing any personal information from your source +document properties. + + + +\subsection{Format of Electronic Manuscript} +\label{sect:pdf} + +For the production of the electronic manuscript you must use Adobe's +Portable Document Format (PDF). This format can be generated from +postscript files. On Linux/Unix systems, you can use {\tt ps2pdf} for +this purpose. In Microsoft Windows, you can use Adobe's Distiller +or GSview (File$<$Convert$<$pdfwrite); if you have \textit{cygwin} +installed, you can use \textit{dvipdf} or \textit{ps2pdf}. Note that +some word processing programs generate PDF which may not include all +the necessary fonts (esp. tree diagrams, symbols). When you print or +create the PDF file, there is usually an option in your printer setup +to include none, all or just non-standard fonts. Please make sure +that you select the option of including ALL the fonts. {\em Before +sending it, test your PDF by printing it from a computer different +from the one where it was created.} Moreover, some word processors may +generate very large postscript/PDF files, where each page is rendered +as an image. Such images may reproduce poorly. In this case, try +alternative ways to obtain the postscript and/or PDF. One way on some +systems is to install a driver for a postscript printer, send your +document to the printer specifying ``Output to a file'', then convert +the file to PDF. + +It is of utmost importance to specify the A4 format (21 cm +x 29.7 cm) when formatting the paper. When working with +{\tt dvips}, for instance, one should specify {\tt -t a4}. + +Print-outs of the PDF file on A4 paper should be identical to the +hardcopy version. If you cannot meet the above requirements about the +production of your electronic submission, please contact the +publication chairs above as soon as possible. + + +\subsection{Layout} +\label{ssec:layout} + +Format manuscripts two columns to a page, in the manner these +instructions are formatted. The exact dimensions for a page on A4 +paper are: + +\begin{itemize} +\item Left and right margins: 2.5 cm +\item Top margin: 2.5 cm +\item Bottom margin: 2.5 cm +\item Column width: 7.7 cm +\item Column height: 24.7 +\item Gap between columns: 0.6 cm +\end{itemize} + +Papers should not be formatted for any other paper size. +% Removed by KO we are not accepting printed papers any more!!! +% Exceptionally, +% authors for whom it is \emph{impossible} to print on A4 paper may use +% \emph{US Letter} paper. In this case, they should keep the \emph{top} +% and \emph{left} margins as given above, use the same column width, +% height and gap, and modify the bottom and right margins as +% necessary. Note that the text will no longer be centered. + +\subsection{Fonts} + +For reasons of uniformity, Adobe's {\bf Times Roman} font should be +used. In \LaTeX2e{} this is accomplished by putting + +\begin{quote} +\begin{verbatim} +\usepackage{times} +\usepackage{latexsym} +\end{verbatim} +\end{quote} +in the preamble. If Times Roman is unavailable, use {\bf Computer + Modern Roman} (\LaTeX2e{}'s default). Note that the latter is about + 10\% less dense than Adobe's Times Roman font. + + +\begin{table}[h] +\begin{center} +\begin{tabular}{|l|rl|} +\hline \bf Type of Text & \bf Font Size & \bf Style \\ \hline +paper title & 15 pt & bold \\ +author names & 12 pt & bold \\ +author affiliation & 12 pt & \\ +the word ``Abstract'' & 12 pt & bold \\ +section titles & 12 pt & bold \\ +document text & 11 pt &\\ +captions & 11 pt & \\ +abstract text & 10 pt & \\ +bibliography & 10 pt & \\ +footnotes & 9 pt & \\ +\hline +\end{tabular} +\end{center} +\caption{\label{font-table} Font guide. } +\end{table} + +\subsection{The First Page} +\label{ssec:first} + +Center the title, author's name(s) and affiliation(s) across both +columns. Do not use footnotes for affiliations. Do not include the +paper ID number assigned during the submission process. Use the +two-column format only when you begin the abstract. + +{\bf Title}: Place the title centered at the top of the first page, in +a 15-point bold font. (For a complete guide to font sizes and styles, see Table~\ref{font-table}.) Long titles should be typed on two lines without +a blank line intervening. Approximately, put the title at 2.5 cm from +the top of the page, followed by a blank line, then the author's +names(s), and the affiliation on the following line. Do not use only +initials for given names (middle initials are allowed). Do not format surnames +in all capitals (e.g., use ``Schlangen'' not ``SCHLANGEN''). +Do not format title and section headings in all capitals as well +except for proper names (such as ``BLEU'') that are conventionally +in all capitals. +The affiliation should contain the author's complete address, and if +possible, an electronic mail address. Leave about 2 cm between the +affiliation and the body of the first page. +The title, author names and addresses should be completely +identical to those entered to the electronical paper submission +website in order to maintain the consistency of author information +among all publications of the conference. + +{\bf Abstract}: Type the abstract at the beginning of the first +column. The width of the abstract text should be smaller than the +width of the columns for the text in the body of the paper by about +0.6 cm on each side. Center the word {\bf Abstract} in a 12 point bold +font above the body of the abstract. The abstract should be a concise +summary of the general thesis and conclusions of the paper. It should +be no longer than 200 words. + +{\bf Text}: Begin typing the main body of the text immediately after +the abstract, observing the two-column format as shown in +the present document. + +{\bf Indent} when starting a new paragraph. Use 11 points for text and +subsection headings, 12 points for section headings and 15 points for +the title. + +\subsection{Sections} + +{\bf Headings}: Type and label section and subsection headings in the +style shown on the present document. Use numbered sections (Arabic +numerals) in order to facilitate cross references. Number subsections +with the section number and the subsection number separated by a dot, +in Arabic numerals. + +{\bf Citations}: Citations within the text appear +in parentheses as~\cite{Gusfield:97} or, if the author's name appears in +the text itself, as Gusfield~\shortcite{Gusfield:97}. +Append lowercase letters to the year in cases of ambiguity. +Treat double authors by using both authors' last names (e.g., +\cite{Aho:72}, but use \emph{et al.} when more than two authors are +involved. (e.g. \cite{Chandra:81}) +Collapse multiple citations (e.g., \cite{Gusfield:97,Aho:72}.) Also +refrain from using full citations as sentence constituents. We suggest +that instead of +\begin{quote} + ``\cite{Gusfield:97} showed that ...'' +\end{quote} +you use +\begin{quote} +``Gusfield \shortcite{Gusfield:97} showed that ...'' +\end{quote} + +If you are using the provided \LaTeX{} and Bib\TeX{} style files, you +can use the command \verb|\newcite| to get ``author (year)'' citations. + +As reviewing will be double-blind, the submitted version of the papers should not include the +authors' names and affiliations. Furthermore, self-references that +reveal the author's identity, e.g., +\begin{quote} +``We previously showed \cite{Gusfield:97} ...'' +\end{quote} +should be avoided. Instead, use citations such as +\begin{quote} +``Gusfield \shortcite{Gusfield:97} +previously showed ... '' +\end{quote} + +Please do not use anonymous +citations and do not include acknowledgements when submitting your papers. Papers that do not conform +to these requirements may be rejected without review. + +\textbf{References}: Gather the full set of references together under +the heading {\bf References}; place the section before any Appendices, +unless they contain references. Arrange the references alphabetically +by first author, rather than by order of occurrence in the text. +Provide as complete a citation as possible, using a consistent format, +such as the one for {\em Computational Linguistics\/} or the one in the +{\em Publication Manual of the American +Psychological Association\/}~\cite{APA:83}. Use of full names for +authors rather than initials is preferred. A list of abbreviations +for common computer science journals can be found in the ACM +{\em Computing Reviews\/}~\cite{ACM:83}. + +The \LaTeX{} and Bib\TeX{} style files provided roughly fit the +American Psychological Association format, allowing regular citations, +short citations and multiple citations as described above. + +{\bf Appendices}: Appendices, if any, directly follow the text and the +references (but see above). Letter them in sequence and provide an +informative title: {\bf Appendix A. Title of Appendix}. + +\textbf{Acknowledgement} section should go as a last section immediately +before the references. Do not number the acknowledgement section. + +\subsection{Footnotes} + +{\bf Footnotes}: Put footnotes at the bottom of the page and use 9 +points text. They may be numbered or referred to by asterisks or other +symbols.\footnote{This is how a footnote should appear.} Footnotes +should be separated from the text by a line.\footnote{Note the line +separating the footnotes from the text.} + +\subsection{Graphics} + +{\bf Illustrations}: Place figures, tables, and photographs in the +paper near where they are first discussed, rather than at the end, if +possible. Wide illustrations may run across both columns. Color +illustrations are discouraged, unless you have verified that +they will be understandable when printed in black ink. + +{\bf Captions}: Provide a caption for every illustration; number each one +sequentially in the form: ``Figure 1. Caption of the Figure.'' ``Table 1. +Caption of the Table.'' Type the captions of the figures and +tables below the body, using 11 point text. + +\section{Translation of non-English Terms} + +It is also advised to supplement non-English characters and terms +with appropriate transliterations and/or translations +since not all readers understand all such characters and terms. +Inline transliteration or translation can be represented in +the order of: original-form transliteration ``translation''. + +\section{Length of Submission} +\label{sec:length} + +Long papers may consist of up to 8 pages of content (excluding references), +and short papers may consist of up to 4 pages of content (excluding references). +Both long and short papers may include any additional number of pages consisting +\emph{solely} of references. +(Appendices count against the eight or four pages, not the additional references pages). +All illustrations, references, and appendices must be +accommodated within these page limits, observing the formatting +instructions given in the present document. Papers that do not +conform to the specified length and formatting requirements are +subject to be rejected without review. + + +\section*{Acknowledgments} + +Do not number the acknowledgment section. Do not include this section +when submitting your paper for review. +%\bibliographystyle{acl} +% you bib file should really go here +%\bibliography{acl2010} + +\begin{thebibliography}{} + +\bibitem[\protect\citename{Aho and Ullman}1972]{Aho:72} +Alfred~V. Aho and Jeffrey~D. Ullman. +\newblock 1972. +\newblock {\em The Theory of Parsing, Translation and Compiling}, volume~1. +\newblock Prentice-{Hall}, Englewood Cliffs, NJ. + +\bibitem[\protect\citename{{American Psychological Association}}1983]{APA:83} +{American Psychological Association}. +\newblock 1983. +\newblock {\em Publications Manual}. +\newblock American Psychological Association, Washington, DC. + +\bibitem[\protect\citename{{Association for Computing Machinery}}1983]{ACM:83} +{Association for Computing Machinery}. +\newblock 1983. +\newblock {\em Computing Reviews}, 24(11):503--512. + +\bibitem[\protect\citename{Chandra \bgroup et al.\egroup }1981]{Chandra:81} +Ashok~K. Chandra, Dexter~C. Kozen, and Larry~J. Stockmeyer. +\newblock 1981. +\newblock Alternation. +\newblock {\em Journal of the Association for Computing Machinery}, + 28(1):114--133. + +\bibitem[\protect\citename{Gusfield}1997]{Gusfield:97} +Dan Gusfield. +\newblock 1997. +\newblock {\em Algorithms on Strings, Trees and Sequences}. +\newblock Cambridge University Press, Cambridge, UK. + +\end{thebibliography} + +\end{document} diff --git a/papers/2010_semeval_hermit/figures/hermit-score-comparison.eps b/papers/2010_semeval_hermit/figures/hermit-score-comparison.eps new file mode 100644 index 00000000..bb5d2164 --- /dev/null +++ b/papers/2010_semeval_hermit/figures/hermit-score-comparison.eps @@ -0,0 +1,945 @@ +%!PS-Adobe-2.0 EPSF-2.0 +%%Title: hermit-score-comparison.eps +%%Creator: gnuplot 4.3 patchlevel 0 +%%CreationDate: Sat May 15 01:56:17 2010 +%%DocumentFonts: (atend) +%%BoundingBox: 50 50 410 302 +%%EndComments +%%BeginProlog +/gnudict 256 dict def +gnudict begin +% +% The following true/false flags may be edited by hand 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V +1080 3518 M +334 -390 V +334 -401 V +335 -626 V +334 -416 V +334 -236 V +334 -36 V +335 -93 V +334 -25 V +334 -16 V +334 5 V +334 -15 V +335 0 V +334 -26 V +334 16 V +1080 3518 Circle +1414 3128 Circle +1748 2727 Circle +2083 2101 Circle +2417 1685 Circle +2751 1449 Circle +3085 1413 Circle +3420 1320 Circle +3754 1295 Circle +4088 1279 Circle +4422 1284 Circle +4756 1269 Circle +5091 1269 Circle +5425 1243 Circle +5759 1259 Circle +5151 2273 Circle +% End plot #2 +1.000 UL +LTb +1080 3780 N +0 -2773 V +4679 0 V +0 2773 V +-4679 0 V +Z stroke +1.000 UP +1.000 UL +LTb +stroke +grestore +end +showpage +%%Trailer +%%DocumentFonts: Helvetica diff --git a/papers/2010_semeval_hermit/figures/results.dat b/papers/2010_semeval_hermit/figures/results.dat new file mode 100644 index 00000000..d9993709 --- /dev/null +++ b/papers/2010_semeval_hermit/figures/results.dat @@ -0,0 +1,16 @@ +#window f-score v-measure num_clusters +1 0.262571 0.163 10.8733 0.5818 +2 0.292162 0.137667 9.51 0.5712 +3 0.356297 0.111667 6.95 0.5646 +4 0.519904 0.071 4.17667 0.5632 +5 0.583416 0.044 2.69333 0.564 +6 0.604408 0.0286667 2.13333 0.565 +7 0.612119 0.0263333 1.92 0.5672 +8 0.614718 0.0203333 1.81667 0.5666 +9 0.617181 0.0186667 1.67333 0.5642 +10 0.619423 0.0176667 1.65333 0.5676 +11 0.619734 0.018 1.66 0.5648 +12 0.620535 0.017 1.58 0.5656 +13 0.619847 0.017 1.61 0.5652 +14 0.620688 0.0153333 1.56333 0.5668 +15 0.621186 0.0163333 1.55333 0.569 diff --git a/papers/2010_semeval_hermit/figures/score-comparison.p b/papers/2010_semeval_hermit/figures/score-comparison.p new file mode 100644 index 00000000..c29b7780 --- /dev/null +++ b/papers/2010_semeval_hermit/figures/score-comparison.p @@ -0,0 +1,55 @@ +set term postscript eps enhanced color lw 3 "Helvetica" 24 +set output 'hermit-score-comparison.eps' +#set terminal png transparent nocrop enhanced font arial 8 size 500,350 +#set output 'hermit-score-comparison.png' + +set multiplot +set bmargin at screen 0.95 +set tmargin at screen 0.8 +set lmargin at screen 0.15 +set rmargin at screen 0.8 # need room for labels + + +set origin 0.0, 0.7 +#set size 0.878, 0.3 +set size 1.0, 0.25 + +#unset xtics +set format x "" +set yrange [0 : 12] noreverse nowriteback +set xrange[1: 15] noreverse nowriteback +set ytics 0, 4 +set ylabel 'Clusters' +set xtics nomirror + +plot 'results.dat' using 1:4 title 'Clusters' with linespoints lc rgb "blue" pt 8 + +set origin 0.0, 0.0 +set size 1.0, .5 +set bmargin at screen 0.75 +set tmargin at screen 0.2 +set xtics mirror +set format x "%2.0f" +set format y "%.2f" +set format y2 "%.2f" + +# move the key out of the way +set key inside right center vertical noreverse enhanced autotitles nobox + +#set style histogram clustered gap 1 title offset character 0, 0, 0 + +#set title "F-Score and V-Measure comparison for different window sizes" +set ylabel "F-Score" +set y2label "V-Measure" +set xlabel 'Window Size' +set yrange [ 0.25 : 0.64 ] noreverse nowriteback +set y2range [ 0.0 : 0.18 ] noreverse nowriteback +#set ytics 0,.1 + +set xrange [ 1 : 15 ] noreverse nowriteback +set y2tics auto +set ytics auto nomirror + +plot 'results.dat' using 1:2 title "F-Score" ls 1 pt 4 lw 1 axis x1y1 with linespoints, \ +'results.dat' using 1:3 title "V-Measure" ls 2 pt 6 lw 1 axis x1y2 with linespoints + diff --git a/papers/2010_semeval_hermit/semeval_2010-no-word-ordering.tex b/papers/2010_semeval_hermit/semeval_2010-no-word-ordering.tex new file mode 100644 index 00000000..555eeb6c --- /dev/null +++ b/papers/2010_semeval_hermit/semeval_2010-no-word-ordering.tex @@ -0,0 +1,376 @@ +\documentclass[11pt,a4]{article} +\usepackage{acl2010} +\usepackage{times} +\usepackage{url} +\usepackage{latexsym} +\usepackage{epsfig} +\usepackage{latexsym} +\usepackage[usenames]{color} +\usepackage{times} +\usepackage{verbatim} +\usepackage{multirow} + +\begin{document} + +\author{David Jurgens\\ + University of California, Los Angeles\\ + Los Angeles, California, USA\\ + {\tt jurgens@cs.ucla.edu} \And + Keith Stevens \\ + University of California, Los Angeles\\ + Los Angeles, California, USA\\ + {\tt kstevens@cs.ucla.edu}} + +\title{ + HERMIT: Flexible Clustering for the SemEval-2 WSI Task} + +\date{} + +\maketitle + +\begin{abstract} + +A single word may have multiple unspecified meanings in a corpus. Word sense +induction aims to discover these different meanings through word use, and +knowledge-lean algorithms attempt this without using external lexical resources. +We propose a new method for identifying the different senses that uses a +flexible clustering strategy to automatically determine the number of senses, +rather than predefining it. We demonstrate the effectiveness using the +SemEval-2 WSI task, achieving competitive scores on both the V-Measure and +Recall metrics, depending on the parameter configuration. + +\end{abstract} + +\section{Introduction} + +The Word Sense Induction task of SemEval 2010 compares several sense induction +and discrimination systems that are trained over a common corpus. Systems are +provided with an unlabeled training corpus consisting of 879,807 contexts for +100 polysemous words, with 50 nouns and 50 verbs. Each context +consists of several sentences that use a single sense of a target word, where at +least one sentence contains the word. Systems must use the training corpus to +induce sense representations for the many word senses +and then use those representations to produce sense labels for the same 100 +words in unseen contexts from a testing corpus. + +We perform this task by utilizing a distributional word space formed using +dimensionality reduction and a hybrid clustering method. Our model is highly +scalable; the dimensionality of the word space is reduced immediately through a +process based on random projections. In addition, an online part of our +clustering algorithm maintains only a centroid that describes an induced word +sense, instead of all observed contexts, which lets the model scale to much +larger corpora than those used in the SemEval-2 WSI task. + +\section{The Word Sense Induction Model} +\label{sec:alg} + +We perform word sense induction by modeling individual contexts in a high +dimensional word space. +Word senses are induced by finding contexts which are similar and therefore +likely to use the same sense of the target word. We use a hybrid clustering +method to group similar contexts. + +\subsection{Modeling Context} +\label{sec:context} + +For a word, each of its contexts are represented by the words with which it +co-occurs. We approximate this high dimensional co-occurrence space with the +Random Indexing (RI) word space model \cite{kanerva00random}. RI represents the +occurrence of a word with an \emph{index vector}, rather than a set of +dimensions. An index vector is a fixed, sparse vector that is orthogonal to all +other words' index vectors with a high probability; the total number of +dimensions in the model is fixed at a small value, e.g.\ 5,000. Orthogonality +is obtained by setting a small percentage of the vector's values to $\pm1$ and +setting the rest to $0$. + +A context is represented by summing the index vectors corresponding to the $n$ +words occurring to the left and right of the polysemous word. +Each occurrence of the polysemous word in the entire corpus is treated as a +separate context. +Contexts are represented by a compact first-order occurrence vector; using index +vectors to represent the occurrences avoids the computational overhead of other +dimensional reduction techniques such as the SVD. + +\subsection{Identifying Related Contexts} +\label{sec:clustering} + +Clustering separates similar context vectors into dissimilar clusters that +represent the distinct senses of a word. We use an efficient hybrid of online +K-Means and Hierarchical Agglomerative Clustering (HAC) with a threshold. The +threshold allows for the final number of clusters to be determined by data +similarity instead of having to specify the number of clusters. + +The set of context vectors for a word are clustered using K-Means, which +assigns a context to the most similar cluster centroid. If the nearest centroid +has a similarity less than the \emph{cluster threshold} and there are not $K$ +clusters, the context forms a new cluster. We define the similarity between +contexts vectors as the cosine similarity. + +Once the corpus has been processed, clusters are repeatedly merged using HAC +with the average link criteria, following \cite{pedersen97distinguishing}. +Average link clustering defines cluster similarity as the mean cosine similarity +of the pairwise similarity of all data points from each cluster. Cluster +merging stops when the two most similar clusters have a similarity less than the +cluster threshold. Reaching a similarity lower than the cluster threshold +signifies that each cluster represents a distinct word sense. + +\subsection{Applying Sense Labels} + +Before training and evaluating our model, all occurrences of the 100 polysemous +words were stemmed in the corpora. Stemming was required due to a polysemous +word being used in multiple lexical forms, e.g.\ plural, in the corpora. By +stemming, we avoid the need to combine contexts for each of the distinct word +forms during clustering. + +After training our WSI model on the training corpus, we process the test corpus +and label the context for each polysemous word with an induced sense. +% +Each test context is labeled with the name of the cluster whose centroid has the +highest cosine similarity to the context vector. +% +We represent the test contexts in the same method used for training; index +vectors are re-used from training. + + +\section{Evaluation and Results} + +The WSI task evaluated the submitted solutions with two methods of +experimentation: an unsupervised method and a supervised method. The +unsupervised method is measured according to the V-Measure and the F-Score. The +supervised method is measured using recall. + +\subsection{Scoring} + +The first measure used is the V-Measure \cite{rosenberg07vmeasure}, +which compares the clusters of target contexts to word classes. This measure +rates the homogeneity and completeness of a clustering solution. Solutions that +have word clusters formed from one word class are homogeneous; completeness +measures the degree to which a word class is composed of target contexts +allocated to a single cluster. + +The second measure, the F-Score, is an extension from information retrieval +and provides a contrasting evaluation metric by using a different +interpretation of homogeneity and completeness. For the F-Score, the precision +and recall of all possible context pairs are measured, where a word class has +the expected context pairs and a provided solution contains some word pairs that +are correct and others that are unexpected. The F-Score tends to discount +smaller clusters and clusters that cannot be assigned to a word class +\cite{manandhar09semeval}. + +\subsection{Parameter Tuning} + +Previous WSI evaluations provided a test corpus, a set of golden sense labels, +and a scoring mechanism, which allowed models to do parameter tuning prior to +providing a set of sense labels. The SemEval 2010 task provided a trial corpus +that contains contexts for four verbs that are not in the evaluation corpus, +which can be used for training and testing. The trial corpus also came with a +set of golden sense assignments. No golden standard was provided for the +training or test corpora, which limited any parameter tuning. + +HERMIT exposes three parameters: cluster threshold, the maximum number of +clusters and the window size for a context. An initial analysis from the trial +data showed that the window size most affected the scores; small window sizes +resulted in higher V-Measure scores, while larger window sizes maximized the +F-Score. Because +contexts are represented using only first-order features, a smaller window size +should have less overlap, which potentially results in a higher number of +clusters. We opted to maximize the V-Measure score by using a window size of +$\pm 1$. + +Due to the limited number of training instances, our precursory analysis with +the trial data did not show significant differences for the remaining two +parameters; we arbitrarily selected a clustering threshold of {\bf .15} and a +maximum of {\bf 15} clusters per word without any parameter tuning. + +After the release of the testing key, we performed a post-hoc analysis to +evaluate the effects of parameter tuning on the scores. We include two +alternative parameter configurations that were optimized for the F-Score +(HERMIT-F) and the supervised evaluations (HERMIT-S). The HERMIT-F variation +used a threshold of 0.85 and a window size of $\pm 10$ words. The HERMIT-S +variation used a threshold of 0.85 and a window size of $\pm 1$ words. We did +not vary the maximum number of clusters, which was set at 15. + +For each evaluation, we provide the scores of seven systems: the three HERMIT +configurations, the highest and lowest scoring submitted systems, the Most +Frequent Sense (MFS) baseline, and a Random baseline provided by the evaluation +team. We provide the scores for each experiment when evaluating all words, +nouns, and verbs. We also include the system's rank relative to all submitted +systems and the average number of senses generated for each system; our +alternative HERMIT configurations are given no rank. + + +\subsection{Unsupervised Evaluation} + + +\begin{table}[htb] + \small + \center + \begin{tabular}{| l | ccccc | } + \hline + System & All & Nouns & Verbs & Rank & Senses \\ + \hline + HERMIT-S & 16.2 & 16.7 & 15.3 & & 10.83 \\ + HERMIT & 16.1 & 16.7 & 15.6 & 1 & 10.78 \\ + Random & 4.4 & 4.6 & 4.1 & 18 & 4.00 \\ + HERMIT-F & 0.015 & 0.008 & 0.025 & & 1.54 \\ + MFS & 0.0 & 0.0 & 0.0 & 27 & 1.00 \\ + LOW & 0.0 & 0.0 & 0.1 & 28 & 1.01 \\ + \hline + \end{tabular} + \caption{V-Measure for the unsupervised evaluation} + \label{tab:evaluation-v} +\end{table} + +\begin{table}[htb] + \small + \center + \begin{tabular}{| l | ccccc | } + \hline + System & All & Nouns & Verbs & Rank & Senses \\ + \hline + MFS & 63.4 & 57.0 & 72.7 & 1 & 1.00 \\ + HIGH & 63.3 & 57.0 & 72.4 & 2 & 1.02 \\ + HERMIT-F & 62.1 & 56.7 & 69.9 & & 1.54 \\ + Random & 31.9 & 30.4 & 34.1 & 25 & 4.00 \\ + HERMIT & 26.7 & 30.1 & 24.4 & 27 & 10.78 \\ + HERMIT-S & 26.5 & 23.9 & 30.3 & & 10.83 \\ + LOW & 16.1 & 15.8 & 16.4 & 28 & 9.71 \\ + \hline + \end{tabular} + \caption{F-Scores for the unsupervised evaluation} + \label{tab:evaluation-f} +\end{table} + + +The unsupervised evaluation considers a golden sense labeling to be word classes +and a set of induced word senses as clusters of target contexts +\cite{manandhar09semeval}. +% +Tables \ref{tab:evaluation-v} and \ref{tab:evaluation-f} display the results for +the unsupervised evaluation when measured according to the V-Measure and the +F-Score, respectively. Our system provides the best V-Measure of all submitted +systems for this evaluation. This is in part due to the average number of +senses our system generated (10.78), which favors more homogenous clusters. +Conversely, this configuration does poorly when measured by F-Score, which tends +to favor systems that generate fewer senses per word. + +When configured for the F-Score, HERMIT-F performs well; this configuration +would have ranked third for the F-Score if it had been submitted. However, its +performance is also due to the relatively few senses per word it generates, +1.54. The inverse performance of both optimized configurations is reflective of +the contrasting nature of the two performance measures. + +\subsection{Supervised Evaluation} + +\begin{table}[tbh] + \center + \small + \begin{tabular} { | l | cccc |} + \hline + System & All & Noun & Verb & Rank \\ + \hline + HIGH & 62.44 & 59.43 & 66.82 & 1 \\ + MFS & 58.67 & 53.22 & 66.620 & 15 \\ + HERMIT-S & 58.48 & 54.18 & 64.78 & \\ + HERMIT & 58.34 & 53.56 & 65.30 & 17 \\ + Random & 57.25 & 51.45 & 65.69 & 19 \\ + HERMIT-F & 56.44 & 53.00 & 61.46 & \\ + LOW & 18.72 & 1.55 & 43.76 & 28 \\ + \hline + \end{tabular} + \caption{Supervised recall for the 80/20 split} + \label{tab:evaluation-80} +\end{table} + +\begin{table}[tbh] + \center + \small + \begin{tabular} { | l | cccc |} + \hline + System & All & Noun & Verb & Rank \\ + \hline + HIGH & 61.96 & 58.62 & 66.82 & 1 \\ + MFS & 58.25 & 52.45 & 67.11 & 12 \\ + HERMIT & 57.27 & 52.53 & 64.16 & 18 \\ + HERMIT-S & 57.10 & 52.76 & 63.46 & \\ + Random & 56.52 & 50.21 & 65.73 & 20 \\ + HERMIT-F & 56.18 & 52.26 & 61.88 & \\ + LOW & 18.91 & 1.52 & 44.23 & 28 \\ + \hline + \end{tabular} + \caption{Supervised recall for the 60/40 split} + \label{tab:evaluation-60} +\end{table} + +The supervised evaluation simulates a supervised Word Sense Disambiguation (WSD) +task. The induced sense labels for the test corpus are split such that the +first set is used for mapping induced senses to golden senses and the remaining +sense labels are treated as sense labels provided by a WSD system, which allows +for evaluation. Five splits are done at random to avoid any biases created due +to the separation of the mapping corpus and the evaluation corpus; the resulting +score for this task is the average recall over the five divisions. Two sets of +splits were used for evaluation: one with 80\% of the senses as the mapping +portion and 20\% as the evaluation portion and one with 60\% as the mapping +portion corpus and 40\% for evaluation. + +The results for the 80/20 split and 60/40 split are displayed in tables +\ref{tab:evaluation-80} and \ref{tab:evaluation-60}, respectively. In both +supervised evaluations, our submitted system does moderately well. In both +cases it outperforms the Random baseline and does almost as well as the MFS +baseline. The submitted system outperforms the Random baseline and approaches +the MFS baseline for the 80/20 split. The HERMIT-S version, which is optimized +for this task, provides similar results. + +\section{Discussion} +\begin{figure} + \vspace{-1mm} + \center \includegraphics[width=.5\textwidth]{figures/hermit-score-comparison.eps} + \vspace{-10mm} + \caption{ + A comparison for F-Score and V-Measure for different window sizes. + Scores are an average using thresholds of 0.15, 0.55 and 0.75.} + \label{fig:algorithm} + \vspace{-1mm} +\end{figure} + +The HERMIT system is easily configured to achieve close to state of the art +performance for either evaluation measure on the unsupervised benchmark. This +reconfigurability allows the algorithm to be tuned for producing a few coarse +senses of a word, or many finer-grained senses. + +We further investigated the performance with respect to the window size +parameter on both measures. Since each score can be effectively optimized +individually, we considered whether both scores could be maximized concurrently. +Figure \ref{fig:algorithm} presents the impact of the window size on both +measures using an average of three threshold parameter configurations. + +The analysis of both measures indicates that reasonable performance can be +obtained from using a slightly larger context window. For example, a window +size of 4 has an average F-Score of 52.4 and V-Measure of 7.1. Although this +configuration produces scores lower than the optimized versions, its performance +would have ranked 12th according to V-Measure and 15th for F-Score. These +scores are consistent with the median performance of the submitted systems and +offer a middle ground should a HERMIT user want a compromise between many +fine-grained word senses and a few coarse-grained word senses. + +\section{Conclusion} + +We have shown that our model is a highly flexible and tunable Word Sense +Induction model. Depending on the task, it can be optimized to generate a set +of word senses that range from being broad and representative to highly +refined. +Furthermore, we demonstrated a balanced performance setting for both measures for +when parameter tuning is not possible. +The model we submitted and presented is only one possible configuration +available, and in the future we will be exploring the effect of other context +features, such as syntactic structure in the form of word ordering +\cite{sahlgren08permutations} or dependency parse trees, % +\cite{pado07dependency}, and other clustering algorithms. Last, this model is +provided as part of the S-Space Package \cite{jurgens10sspace}, an open +source toolkit for word space algorithms. + + +\bibliographystyle{acl} +\bibliography{semeval_2010} + +\end{document} diff --git a/papers/2010_semeval_hermit/semeval_2010.bib b/papers/2010_semeval_hermit/semeval_2010.bib new file mode 100644 index 00000000..8686504e --- /dev/null +++ b/papers/2010_semeval_hermit/semeval_2010.bib @@ -0,0 +1,328 @@ +@inproceedings{agirre07semeval, + author = {Eneko Agirre and Aitor Soroa}, + title = {Semeval-2007 task 02: {E}valuating word sense induction and discrimination systems}, + booktitle = {Proceedings of the Fourth International Workshop on Semantic Evaluations}, + pages = {7--12}, + location = {Prague, Czech Republic}, + month = {June}, + year = 2007, + publisher = {A{C}{L}}, +} + +@inproceedings{baroni07isa, + author = {Marco Baroni and Alessandro Lenci and Luca Onnis}, + year = 2007, + title = {ISA meets Lara: A fully incremental word space model for cognitively plausible simulations of semantic learning}, + booktitle = {Proceedings of the 45th Meeting of the Association for Computational Linguistics}, +} + +@article{baroni10strudel, + author = {Marco Baroni and Brian Murphy and Eduard Barbu and Massimo Poesio}, + title = {Strudel: A corpus-based semantic model based on properties and types}, + journal = {Cognitive Science}, + year = {\emph{to appear}}, +} + +@article{baroni09wacky, + author = {Marco Baroni and Silvia Bernardini and Adriano Ferraresi and Eros Zanchetta}, + year = 2009, + title = {The {W}a{C}ky Wide Web: A Collection of Very Large Linguistically Processed Web-Crawled Corpora}, + journal = {Language Resources and Evaluation}, + volume = 43, + number = 3, + pages = {209-226}, +} + +@inproceedings{basile08combining, + author = {Basile, Pierpaolo and de Gemmis, Marco and Lops, Pasquale and Semeraro, Giovanni}, + title = {Combining knowledge-based methods and supervised learning for effective Italian word sense disambiguation}, + booktitle = {STEP '08: Proceedings of the 2008 Conference on Semantics in Text Processing}, + year = {2008}, + pages = {5--16}, + location = {Venice, Italy}, + publisher = {Association for Computational Linguistics}, + address = {Morristown, NJ, USA}, +} + +@inproceedings{brody09bayesian, + author = {Samuel Brody and Mirella Lapata}, + title = {Bayesian word sense induction}, + booktitle = {Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics}, + pages = {103--111}, + year = 2009, +} + +@article{burgess97modeling, + author = {Curt Burgess and Kevin Lund}, + year = 1997, + title = {Modeling parsing constraints with high-dimensional context space}, + journal = {Language and Cognitive Processes}, + volume = 12, + issue = {2-3}, + pages = {177–210}, +} + +@inproceedings{cutting92scatter, + author = {Douglas Cutting and Jan Pedersen and David Karger and John Tukey}, + year = 1992, + title = {Scatter/Gather: A cluster-based approach to browsing large document collections}, + booktitle = {Proceedings of the 15th Annual International ACM Conference on Research and Development in Information Retrieval (SIGIR)}, + location = {Copenhagen, Denmark}, + pages = {318-329}, +} + +@inproceedings{dligach08novel, + author = {Dmitry Dligach and Martha Palmer}, + title = {Novel Semantic Features for Verb Sense Disambiguation}, + booktitle = {HLT '08: Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies}, + location = {Columbus, Ohio}, + publisher = {Association for Computational Linguistics}, + address = {Morristown, NJ, USA}, + pages = {29--32}, + year = 2008, +} + +@inproceedings{erk08structured, + address = {Honolulu, HI}, + author = {Katrin Erk and Sebastian Pad\'{o}}, + booktitle = {Proceedings of EMNLP}, + title = {A Structured Vector Space Model for Word Meaning in Context}, + year = {2008} +} + +@inbook{harris85distributional, + author = {Zellig Haris}, + title = {Distributional Structure}, + editor = {J. 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Agirre and P. Edmonds}, + booktitle = {Word Sense Disambiguation: Algorithms and applications}, + publiser = {Springer}, + year = 2006, +} + +@inproceedings{purandare04discriminating, + author = {Amruta Purandare and Ted Petersen}, + title = {Discriminating Among Word Meanings by Identifying Similar Contexts}, + booktitle = {Proceedings of the Nineteenth National Conference on Artificial Intelligence (AAAI-04)}, + year = 2004, + pages = {964--965}, +} + +@inproceedings{purandare04word, + author = {Amruta Purandare and Ted Pedersen}, + booktitle = {HLT-NAACL 2004 Workshop: Eighth Conference on Computational Natural Language Learning (CoNLL-2004)}, + pages = {41--48}, + publisher = {Association for Computational Linguistics}, + title = {Word Sense Discrimination by Clustering Contexts in Vector and Similarity Spaces}, + year = {2004} +} + +@inproceedings{rapp03word, + author = {Reinhard Rapp}, + year = 2003, + title = {Word sense discovery based on sense descriptor dissimilarity}, + booktitle = {Ninth Machine Translation Summit}, + address = {New Orleans}, + pages = {315--322}, +} + +@inproceedings{rosenberg07vmeasure, + author = {Andrew Rosenberg and Julia Hirschberg}, + title = {{V-Measure: A Conditional Entropy-Based External Cluster Evaluation Measure}}, + booktitle = {Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL)}, + location = {Prague, Czech Republic}, + month_ignore = {June}, + year = 2007, + publisher = {A{C}{L}}, +} + +@inproceedings{sahlgren01vector, + author = {Magnus Sahlgren}, + title = {{Vector-Based Semantic Analysis: Representing Word Meanings Based on Random Labels}}, + booktitle = {Proceedings of the ESSLLI 2001 Workshop on Semantic Knowledge Acquisition and Categorisation}, + address = {Helsinki, Finland}, + year = 2001, +} + +@inproceedings{sahlgren08permutations, + author = {Magnus Sahlgren and Anders Holst and Pentti Kanerva}, + year = 2008, + title = {Permutations as a Means to Encode Order in Word Space}, + booktitle = {Proceedings of the 30th Annual Meeting of the Cognitive Science Society (CogSci'08)}, + location = {Washington D.C., USA}, +} + +@article{schulte06experiments, + title = {{Experiments on the Automatic Induction of German Semantic Verb Classes}}, + author = {Schulte im Walde, Sabine}, + journal = {Computational Linguistics}, + year = {2006}, + volume = 32, + number = 2, +} + +@inbook{schutze92context, + author = {Hinrich Sch\"{u}tze}, + title = {{Context Space}}, + booktitle = {Working Notes of the AAAI Fall Symposium on Probabilistic Approaches to Natural Language}, + editor = {Robert Goldman and Peter Norvig and Eugene Charniak and Bill Gale}, + year = {1992}, + publisher = {AAAI Press}, + address = {Menlo Park, CA}, + pages = {113--120}, +} + +@article{schutze98automatic, + author = {Hinrich Sch\"{u}tze}, + title = {Automatic Word Sense Discrimination}, + journal = {Computational Linguistics}, + year = {1998}, + volume = 24, + number = 1, + pages = {97--123}, +} + +@article{zhang05improving, + journal = {Neural Processing Letters}, + title = {Improving the Robustness of ‘Online Agglomerative Clustering Method’ Based on Kernel-Induce Distance Measures}, + volume = 21, + issue = 1, + pages = {45 -- 51}, + year = 2005, + author = {Daoqiang Zhang and Songcan Chen and Keren Tan}, +} + +@inproceedings{zhao02clustering, + author = {Zhao, Ying and Karypis, George}, + title = {Evaluation of hierarchical clustering algorithms for document datasets}, + booktitle = {CIKM '02: Proceedings of the eleventh international conference on Information and knowledge management}, + year = {2002}, + isbn = {1-58113-492-4}, + pages = {515--524}, + location = {McLean, Virginia, USA}, + doi = {http://doi.acm.org/10.1145/584792.584877}, + publisher = {ACM}, + address = {New York, NY, USA}, +} + +@article{zhao05hierarchical, + author = {Ying Zhao and George Karypis}, + year = 2005, + title = {Hierarchical clustering algorithms for document datasets}, + journal = {Data Mining and Knowledge Discovery}, + volume = 10, + number = 2, + pages = {141–-168}, +} diff --git a/papers/2010_semeval_hermit/semeval_2010.tex b/papers/2010_semeval_hermit/semeval_2010.tex new file mode 100644 index 00000000..25eb5c5b --- /dev/null +++ b/papers/2010_semeval_hermit/semeval_2010.tex @@ -0,0 +1,315 @@ +\documentclass[11pt]{article} +\usepackage{acl2010} +\usepackage{times} +\usepackage{url} +\usepackage{latexsym} +\usepackage{epsfig} +\usepackage{booktabs} +\usepackage{latexsym} +\usepackage[usenames]{color} +\usepackage{times} +\usepackage{verbatim} +\usepackage{threeparttable} +\usepackage{multirow} + +\begin{document} + +\author{David Jurgens\\ + University of California, Los Angeles\\ + Los Angeles, California, USA\\ + {\tt jurgens@cs.ucla.edu} \And + Keith Stevens \\ + University of California, Los Angeles\\ + Los Angeles, California, USA\\ + {\tt kstevens@cs.ucla.edu}} + +\title{ + HERMIT. Using word ordering applied to the Sense Induction task of SemEval-2} + +\date{} + +\maketitle + +\begin{abstract} +A single word may have multiple unspecified meanings in a corpus. Word sense +induction aims to discover these different meanings through word use, and +knowledge-poor algorithms attempt this without using external lexical resources. +However, the syntactic information available from these resources has been shown +to improve performance. Therefore, we propose a new knowledge-poor model that +uses word order to add a limited form of syntactic information. Three +experiments demonstrate improvement in word sense induction accuracy and state +of the art performance on benchmarks. + +\end{abstract} + +\section{Introduction} + +The Word Sense Induction task of SemEval 2010 is compares several sense +induction and discrimination systems when trained over a common corpus. Systems +are provided with an unlabeled training corpus consisting of XX,XXX contexts for +100 different polysemous words, composed of X nouns and Y verbs. Each context +is composed of several sentences, several of which may contain a polysemous word +that requires a sense label and the sense label of each context is unknown. +Systems must use a training corpus to induce the word senses for each of the 100 +words and then use those senses to label unseen contexts for the same 100 words +from a testing corpus. + +We perform this task by utilizing a distributional word space that is formed by +using word ordering, dimensionality reduction, and a simple clustering method. +We refer to our model as Word Ordering with Reduced Dimensionality for Sense +Induction (WORDSI). Word ordering provides a shallow form of syntactic +information that can be applied to any language and has has previously been +shown to benefit distributional semantics\cite{burgess97modeling}. Our model is +also highly scalable; the dimensionality of the word space is reduced +immediately through a process based on random projections. In addition, our +online clustering algorithm maintains only a centroid that describes an induced +word sense, instead of all observed contexts, which lets the model scale to +large corpora. + +\section{The Word Sense Induction Model} +\label{sec:alg} + +We perform word sense induction by modeling individual contexts in a high +dimensional word space that encodes lexical position. Word senses are induced +by clustering these contexts as they are observed to identify groupings of +similar contexts, under the assumption that contexts with different word +distributions denote a different sense of the word is being used. + +\subsection{Modeling Context} +\label{sec:context} + +For a word, each of its contexts are represented by the words with which it +co-occurs and their respective lexical positions. To fully model this +information, each unique word would be represented with multiple dimensions to +distinguish its occurrence in different lexical positions. +We approximate this high dimensional space with the Random Indexing (RI) word +space model \cite{kanerva00random} with permutations +\cite{sahlgren08permutations}. RI represent the occurrence of a word with an +\emph{index vector}, rather than a set of dimensions. An index vector is a +sparse vector that is highly orthogonal to all other words' index vectors; the +total number of dimensions in the model is fixed at a small value, +e.g. 50,000. A context's word occurrences are represented by summing the index +vectors of the occurring words, projecting the full context information in a +subspace that best preserves the original distances between context vectors. + +We illustrate this with an example. Consider the context for ``check'' in the +phrase ``I could not deposit check due to a bank holiday,''. After stop words +have been removed, the context vector would be the summation of the index +vectors of the co-occurring words, ``deposit,'' ``bank,'' and ``holiday.'' Word +ordering information is added by \emph{permuting} the index vectors based their +respective words' positions: +% + {\small $ + context_{check} = \Pi^{-1}(iv_{deposit}) + \Pi^{4}(iv_{bank}) + + \Pi^{5}(iv_{holiday}) $ }, +% +where $\Pi^i$ is a bijective permutation function that is applied $i$ times to a +vector and $iv_{term}$ is a term's index vector. This creates a unique method +of counting the co-occurrence for each word based on its position. Formally, we +define the context vector, $V$, for an occurrence of term $w$, as +% +$ +V = \sum_{term \in Context} \Pi^{dist(term,w)}(iv_{term}), +$ +% +where $dist(term, w)$ is the lexical distance between $term$ and $w$. Note that +terms preceding $w$ are given a negative distance, which results in an inverse +permutation of their index vectors. + + +\subsection{Identifying Related Contexts} +\label{sec:clustering} + +Clustering separates similar context vectors into dissimilar clusters that +represent the distinct senses of a word. We use an efficient hybrid of online +K-Means and Hierarchical Agglomerative Clustering (HAC) with a threshold. The +threshold allows for the final number of clusters to be determined by data +similarity instead of having to specify the number of clusters. + +The set of context vectors for a word are clustered using using K-Means, which +assigns a context to the most similar cluster centroid. If the nearest centroid +has a similarity less than the \emph{cluster threshold} and there are not $K$ +clusters, the context forms a new cluster. We define the similarity between +contexts vectors as the cosine similarity. + +Once the corpus has been processed, clusters are repeatedly merged using HAC +with the average link criteria, following \cite{pedersen97distinguishing}. +Average link clustering defines cluster similarity as the mean cosine similarity +of the pairwise similarity of all data points from each cluster. Cluster +merging stops when the two most similar clusters have a similarity less than the +cluster threshold. Reaching a similarity lower than the cluster threshold +signifies that each cluster represents a distinct word sense. This approach is +similar in intent to that of Neill \shortcite{neill02fully} +where an upper-bound of $K$ is initially used, but the number of final senses +may be much smaller. + +\section{Applying Sense Labels} + +After training our WSI model on the training corpus, process the test corpus and +label the context for each polysemous word with an induced sense. We represent +the test contexts in the same method used for training; the index vectors and +permutation functions are re-used during training and testing. Each word's +context is then labeled with the induced cluster that has the most similar +representation. + +BIGFUCKINGNOTE somewhere around here. We don't use permutations in the version +we submitted. + +\subsection{Tuning Parameters} + +Previous WSI evaluations provided a test corpus, a set of golden sense labels, +and a scoring mechanism, which allowed models to do parameter tuning prior to +providing a set of sense labels. The SemEval 2010 task is structured such that +a trial corpus is provided, which consists of training contexts, test contexts, +and a set of golden sense assignments for the test contexts. The trial corpus +consists of four polysemous verbs that are not part of the real corpus. The +lack of a golden set of sense labels for the real test corpus presents an issue +for our model, which requires a clustering threshold in addition to a random set +of index vectors and permutation functions. + +Rather than doing parameter tuning on the real corpus, we perform parameter +tuning by utilizing the trial corpus and re-using the clustering threshold, +index vectors, and permutation functions that provided the best trial score. +Based on experiments over the trial corpus, and previous experiments on other +corpora \cite{}, we use a clustering threshold of {\bf .15}, a maximum +of {\bf 15} clusters per word, and a window of $\pm1$. These values showed +reasonable stable scores when different sets of index vectors and permutation +vectors were used. + +The trial corpus does not consist of all the words observed in the real training +and test corpora. The permutation functions are re-used without any +alterations. Any index vectors generated for the trial corpus are re-used, and +the random number generator for the trial corpus is re-used to generate new +index vectors for the training and test corpora. We note that this is the only +information shared between the trial corpus and the evaluation corpus; the word +distributions from the trial corpus are not used during evaluation in any way. + +\section{Results and Discussion} + +The WSI task used experiments to evaluate submitted solutions: an unsupervised +method and a supervised method. The unsupervised method is measured according +to the V-Measure and the F-Score. The supervised method is measured using +precision and recall. Our submitted solution was optimized for the unsupervised +experiment when rated by the V-Measure. For comparison, we include in this +system description alternate versions of our system that are optimized for the +F-Score and the supervised experiment. + +\subsection{Unsupervised Evaluation} + +Intro paragraph here explaining concisely the unsupervised evaluation. Then +explain how the V-Measure \cite{rosenberg07vmeasure} and F-Score differ, and +what they each measure. We should note that the V-Measure tends to favor +systems that generate more clusters whereas the F-Score favors systems that +generate fewer clusters. + +Refer to a table that contains optimized results for the V-Measure and the +F-Score. Be sure to highlight what is interesting about each of them. It would +be best to find a configuration that scores high according to the F-Score but +still has a high number of clusters, i.e., something more than 1.02 (Pedersen's +cluster average). + +\subsection{Supervised Evaluation} + +Intro paragraph here explaining concisely the supervised evaluation. Then +explain how the measurements function, along with the two test splits. + +Refer to a table that contains optimized results for the V-Measure submission +and another submission based on this experiment. Note how they are different. + +We also need to spend a fair amount of time describing how we are different from +others. We can also explore why a context window of 1, as opposed to more, +provides good results. It is also worth noting that permutations only really +gives us a right/left distinction with the window size. + +\begin{table}[htb] + \small + \center + \begin{tabular}{| l | ccccc | } + \hline + System & All & Nouns & Verbs & Rank & Senses \\ + \hline + HERMIT & 16.1 & 15.6 & 16.7 & 1 & 10.78 \\ + WORDSI-F & 26.7 & 30.1 & 24.4 & ? & 10.78 \\ + WORDSI-S & 26.7 & 30.1 & 24.4 & ? & 10.78 \\ + Random & 4.4 & 4.6 & 4.1 & ? & 4 \\ + MFS & 0.0, & 0.0 & 0.0 & ? & 1.0 \\ + LOW & 0.0 & 0.1 & 0.0 & ? & 1.01 \\ + \hline + \end{tabular} + \caption{V-Measure} + \label{tab:evaluation} +\end{table} + +\begin{table}[htb] + \small + \center + \begin{tabular}{| l | ccccc | } + \hline + System & All & Nouns & Verbs & Rank & Senses \\ + \hline + MFS & 63.4 & 72.7 & 57.0 & 1 & 1 \\ + Random & 31.9 & 34.1 & 30.4 & ? & 4 \\ + HERMIT & 26.7 & 30.1 & 24.4 & ? & 10.78 \\ + WORDSI-F & 26.7 & 30.1 & 24.4 & ? & 10.78 \\ + WORDSI-S & 26.7 & 30.1 & 24.4 & ? & 10.78 \\ + LOW & 16.1 & 16.4 & 15.8 & ? & 9.71 \\ + \hline + \end{tabular} + \caption{F-Score} + \label{tab:evaluation} +\end{table} + +\begin{table} + \center + \small + \begin{tabular} { | l | cccc |} + \hline + System & All & Noun & Verb & Rank \\ + \hline + HIGH & 62.44 & 59.43 & 66.82 & 1 \\ + MFS & 58.67 & 53.22 & 66.620 & ? \\ + WORDSI-F & 58.34 & 53.56 & 65.30 & ? \\ + WORDSI-S & 58.34 & 53.56 & 65.30 & ? \\ + HERMIT & 58.34 & 53.56 & 65.30 & ? \\ + Random & 57.25 & 51.45 & 65.69 & ? \\ + LOW & 18.72 & 1.55 & 43.76 & ? \\ + \hline + \end{tabular} + \caption{Scores for SemEval Task 2 Supervised Evaluation, ordered by recall} + \label{tab:supervised-sem07} +\end{table} + +\begin{table} + \center + \small + \begin{tabular} { | l | cccc |} + \hline + System & All & Noun & Verb & Rank \\ + \hline + HIGH & 61.96 & 58.62 & 66.82 & 1 \\ + MFS & 58.25 & 52.45 & 67.11 & ? \\ + WORDSI-F & 58.34 & 53.56 & 65.30 & ? \\ + WORDSI-S & 58.34 & 53.56 & 65.30 & ? \\ + HERMIT & 57.27 & 52.53 & 64.16 & ? \\ + Random & 56.52 & 50.21 & 65.73 & ? \\ + LOW & 18.91 & 1.52 & 44.23 & ? \\ + \hline + \end{tabular} + \caption{Scores for SemEval Task 2 Supervised Evaluation, ordered by recall} + \label{tab:supervised} +\end{table} + +\section{Conclusion} + +The syntactic information in word-ordering improves WSI accuracy when used with +co-occurrence features. Our results show that adding word-ordering results in +state-of-the-art performance on a standard WSI benchmark. Furthermore, the WSI +accuracy gains from word-ordering were shown to be present in two languages. +In future work, we will consider other clustering techniques, and investigate +the impact of specific positions. This model will also be provided as part +of an open source toolkit for Word Space Algorithms. + +\bibliographystyle{acl} +\bibliography{semeval_2010} + +\end{document} diff --git a/papers/2011_emnlp_unsup_impact/acl-hlt2011.sty b/papers/2011_emnlp_unsup_impact/acl-hlt2011.sty new file mode 100644 index 00000000..45c70856 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/acl-hlt2011.sty @@ -0,0 +1,343 @@ +% File acl-hlt2011.sty +% October 11, 2004 +% Contact: oflazer@sabanciuniv.edu + +% This is the LaTeX style file for ACL 2005. It is nearly identical to the +% style files for ACL 2002, ACL 2001, ACL 2000, EACL 95 and EACL +% 99. +% +% This is the LaTeX style file for ACL 2000. It is nearly identical to the +% style files for EACL 95 and EACL 99. Minor changes include editing the +% instructions to reflect use of \documentclass rather than \documentstyle +% and removing the white space before the title on the first page +% -- John Chen, June 29, 2000 + +% To convert from submissions prepared using the style file aclsub.sty +% prepared for the ACL 2000 conference, proceed as follows: +% 1) Remove submission-specific information: \whichsession, \id, +% \wordcount, \otherconferences, \area, \keywords +% 2) \summary should be removed. The summary material should come +% after \maketitle and should be in the ``abstract'' environment +% 3) Check all citations. This style should handle citations correctly +% and also allows multiple citations separated by semicolons. +% 4) Check figures and examples. Because the final format is double- +% column, some adjustments may have to be made to fit text in the column +% or to choose full-width (\figure*} figures. +% 5) Change the style reference from aclsub to acl2000, and be sure +% this style file is in your TeX search path + + +% This is the LaTeX style file for EACL-95. It is identical to the +% style file for ANLP '94 except that the margins are adjusted for A4 +% paper. -- abney 13 Dec 94 + +% The ANLP '94 style file is a slightly modified +% version of the style used for AAAI and IJCAI, using some changes +% prepared by Fernando Pereira and others and some minor changes +% by Paul Jacobs. + +% Papers prepared using the aclsub.sty file and acl.bst bibtex style +% should be easily converted to final format using this style. +% (1) Submission information (\wordcount, \subject, and \makeidpage) +% should be removed. +% (2) \summary should be removed. The summary material should come +% after \maketitle and should be in the ``abstract'' environment +% (between \begin{abstract} and \end{abstract}). +% (3) Check all citations. This style should handle citations correctly +% and also allows multiple citations separated by semicolons. +% (4) Check figures and examples. Because the final format is double- +% column, some adjustments may have to be made to fit text in the column +% or to choose full-width (\figure*} figures. + +% Place this in a file called aclap.sty in the TeX search path. +% (Placing it in the same directory as the paper should also work.) + +% Prepared by Peter F. Patel-Schneider, liberally using the ideas of +% other style hackers, including Barbara Beeton. +% This style is NOT guaranteed to work. It is provided in the hope +% that it will make the preparation of papers easier. +% +% There are undoubtably bugs in this style. If you make bug fixes, +% improvements, etc. please let me know. My e-mail address is: +% pfps@research.att.com + +% Papers are to be prepared using the ``acl'' bibliography style, +% as follows: +% \documentclass[11pt]{article} +% \usepackage{acl2000} +% \title{Title} +% \author{Author 1 \and Author 2 \\ Address line \\ Address line \And +% Author 3 \\ Address line \\ Address line} +% \begin{document} +% ... +% \bibliography{bibliography-file} +% \bibliographystyle{acl} +% \end{document} + +% Author information can be set in various styles: +% For several authors from the same institution: +% \author{Author 1 \and ... \and Author n \\ +% Address line \\ ... \\ Address line} +% if the names do not fit well on one line use +% Author 1 \\ {\bf Author 2} \\ ... \\ {\bf Author n} \\ +% For authors from different institutions: +% \author{Author 1 \\ Address line \\ ... \\ Address line +% \And ... \And +% Author n \\ Address line \\ ... \\ Address line} +% To start a seperate ``row'' of authors use \AND, as in +% \author{Author 1 \\ Address line \\ ... \\ Address line +% \AND +% Author 2 \\ Address line \\ ... \\ Address line \And +% Author 3 \\ Address line \\ ... \\ Address line} + +% If the title and author information does not fit in the area allocated, +% place \setlength\titlebox{} right after +% \usepackage{acl2000} +% where can be something larger than 2.25in + +% \typeout{Conference Style for ACL 2000 -- released June 20, 2000} +\typeout{Conference Style for ACL 2005 -- released Octobe 11, 2004} + +% NOTE: Some laser printers have a serious problem printing TeX output. +% These printing devices, commonly known as ``write-white'' laser +% printers, tend to make characters too light. To get around this +% problem, a darker set of fonts must be created for these devices. +% + +% Physical page layout - slightly modified from IJCAI by pj +\setlength\topmargin{0.0in} \setlength\oddsidemargin{-0.0in} +\setlength\textheight{9.0in} \setlength\textwidth{6.5in} +\setlength\columnsep{0.2in} +\newlength\titlebox +\setlength\titlebox{2.25in} +\setlength\headheight{0pt} \setlength\headsep{0pt} +%\setlength\footheight{0pt} +\setlength\footskip{0pt} +\thispagestyle{empty} \pagestyle{empty} +\flushbottom \twocolumn \sloppy + +%% A4 version of page layout +%\setlength\topmargin{-0.45cm} % changed by Rz -1.4 +%\setlength\oddsidemargin{.8mm} % was -0cm, changed by Rz +%\setlength\textheight{23.5cm} +%\setlength\textwidth{15.8cm} +%\setlength\columnsep{0.6cm} +%\newlength\titlebox +%\setlength\titlebox{2.00in} +%\setlength\headheight{5pt} +%\setlength\headsep{0pt} +%%\setlength\footheight{0pt} +%\setlength\footskip{0pt} +%\thispagestyle{empty} +%\pagestyle{empty} + +\flushbottom \twocolumn \sloppy + +% We're never going to need a table of contents, so just flush it to +% save space --- suggested by drstrip@sandia-2 +\def\addcontentsline#1#2#3{} + +% Title stuff, taken from deproc. +\def\maketitle{\par + \begingroup + \def\thefootnote{\fnsymbol{footnote}} + \def\@makefnmark{\hbox to 0pt{$^{\@thefnmark}$\hss}} + \twocolumn[\@maketitle] \@thanks + \endgroup + \setcounter{footnote}{0} + \let\maketitle\relax \let\@maketitle\relax + \gdef\@thanks{}\gdef\@author{}\gdef\@title{}\let\thanks\relax} +\def\@maketitle{\vbox to \titlebox{\hsize\textwidth + \linewidth\hsize \vskip 0.125in minus 0.125in \centering + {\Large\bf \@title \par} \vskip 0.2in plus 1fil minus 0.1in + {\def\and{\unskip\enspace{\rm and}\enspace}% + \def\And{\end{tabular}\hss \egroup \hskip 1in plus 2fil + \hbox to 0pt\bgroup\hss \begin{tabular}[t]{c}\bf}% + \def\AND{\end{tabular}\hss\egroup \hfil\hfil\egroup + \vskip 0.25in plus 1fil minus 0.125in + \hbox to \linewidth\bgroup\large \hfil\hfil + \hbox to 0pt\bgroup\hss \begin{tabular}[t]{c}\bf} + \hbox to \linewidth\bgroup\large \hfil\hfil + \hbox to 0pt\bgroup\hss \begin{tabular}[t]{c}\bf\@author + \end{tabular}\hss\egroup + \hfil\hfil\egroup} + \vskip 0.3in plus 2fil minus 0.1in +}} +\renewenvironment{abstract}{\centerline{\large\bf + Abstract}\vspace{0.5ex}\begin{quote} \small}{\par\end{quote}\vskip 1ex} + + +% bibliography + +\def\thebibliography#1{\section*{References} + \global\def\@listi{\leftmargin\leftmargini + \labelwidth\leftmargini \advance\labelwidth-\labelsep + \topsep 1pt plus 2pt minus 1pt + \parsep 0.25ex plus 1pt \itemsep 0.25ex plus 1pt} + \list {[\arabic{enumi}]}{\settowidth\labelwidth{[#1]}\leftmargin\labelwidth + \advance\leftmargin\labelsep\usecounter{enumi}} + \def\newblock{\hskip .11em plus .33em minus -.07em} + \sloppy + \sfcode`\.=1000\relax} + +\def\@up#1{\raise.2ex\hbox{#1}} + +% most of cite format is from aclsub.sty by SMS + +% don't box citations, separate with ; and a space +% also, make the penalty between citations negative: a good place to break +% changed comma back to semicolon pj 2/1/90 +% \def\@citex[#1]#2{\if@filesw\immediate\write\@auxout{\string\citation{#2}}\fi +% \def\@citea{}\@cite{\@for\@citeb:=#2\do +% {\@citea\def\@citea{;\penalty\@citeseppen\ }\@ifundefined +% {b@\@citeb}{{\bf ?}\@warning +% {Citation `\@citeb' on page \thepage \space undefined}}% +% {\csname b@\@citeb\endcsname}}}{#1}} + +% don't box citations, separate with ; and a space +% Replaced for multiple citations (pj) +% don't box citations and also add space, semicolon between multiple citations +\def\@citex[#1]#2{\if@filesw\immediate\write\@auxout{\string\citation{#2}}\fi + \def\@citea{}\@cite{\@for\@citeb:=#2\do + {\@citea\def\@citea{; }\@ifundefined + {b@\@citeb}{{\bf ?}\@warning + {Citation `\@citeb' on page \thepage \space undefined}}% + {\csname b@\@citeb\endcsname}}}{#1}} + +% Allow short (name-less) citations, when used in +% conjunction with a bibliography style that creates labels like +% \citename{, } +% +\let\@internalcite\cite +\def\cite{\def\citename##1{##1, }\@internalcite} +\def\shortcite{\def\citename##1{}\@internalcite} +\def\newcite{\def\citename##1{{\frenchspacing##1} (}\@internalciteb} + +% Macros for \newcite, which leaves name in running text, and is +% otherwise like \shortcite. +\def\@citexb[#1]#2{\if@filesw\immediate\write\@auxout{\string\citation{#2}}\fi + \def\@citea{}\@newcite{\@for\@citeb:=#2\do + {\@citea\def\@citea{;\penalty\@m\ }\@ifundefined + {b@\@citeb}{{\bf ?}\@warning + {Citation `\@citeb' on page \thepage \space undefined}}% +{\csname b@\@citeb\endcsname}}}{#1}} +\def\@internalciteb{\@ifnextchar [{\@tempswatrue\@citexb}{\@tempswafalse\@citexb[]}} + +\def\@newcite#1#2{{#1\if@tempswa, #2\fi)}} + +\def\@biblabel#1{\def\citename##1{##1}[#1]\hfill} + +%%% More changes made by SMS (originals in latex.tex) +% Use parentheses instead of square brackets in the text. +\def\@cite#1#2{({#1\if@tempswa , #2\fi})} + +% Don't put a label in the bibliography at all. Just use the unlabeled format +% instead. +\def\thebibliography#1{\small\vskip\parskip% +\vskip\baselineskip% +\def\baselinestretch{1}% +\ifx\@currsize\normalsize\@normalsize\else\@currsize\fi% +\vskip-\parskip% +\vskip-\baselineskip% +\section*{References\@mkboth + {References}{References}}\list + {}{\setlength{\labelwidth}{0pt}\setlength{\leftmargin}{\parindent} + \setlength{\itemsep}{-0.5ex} + \setlength{\itemindent}{-\parindent}} + \def\newblock{\hskip .11em plus .33em minus -.07em} + \sloppy\clubpenalty4000\widowpenalty4000 + \sfcode`\.=1000\relax} +\let\endthebibliography=\endlist + +% Allow for a bibliography of sources of attested examples +\def\thesourcebibliography#1{\vskip\parskip% +\vskip\baselineskip% +\def\baselinestretch{1}% +\ifx\@currsize\normalsize\@normalsize\else\@currsize\fi% +\vskip-\parskip% +\vskip-\baselineskip% +\section*{Sources of Attested Examples\@mkboth + {Sources of Attested Examples}{Sources of Attested Examples}}\list + {}{\setlength{\labelwidth}{0pt}\setlength{\leftmargin}{\parindent} + \setlength{\itemindent}{-\parindent}} + \def\newblock{\hskip .11em plus .33em minus -.07em} + \sloppy\clubpenalty4000\widowpenalty4000 + \sfcode`\.=1000\relax} +\let\endthesourcebibliography=\endlist + +\def\@lbibitem[#1]#2{\item[]\if@filesw + { \def\protect##1{\string ##1\space}\immediate + \write\@auxout{\string\bibcite{#2}{#1}}\fi\ignorespaces}} + +\def\@bibitem#1{\item\if@filesw \immediate\write\@auxout + {\string\bibcite{#1}{\the\c@enumi}}\fi\ignorespaces} + +% sections with less space +\def\section{\@startsection {section}{1}{\z@}{-2.0ex plus + -0.5ex minus -.2ex}{1.5ex plus 0.3ex minus .2ex}{\large\bf\raggedright}} +\def\subsection{\@startsection{subsection}{2}{\z@}{-1.8ex plus + -0.5ex minus -.2ex}{0.8ex plus .2ex}{\normalsize\bf\raggedright}} +\def\subsubsection{\@startsection{subsubsection}{3}{\z@}{1.5ex plus + 0.5ex minus .2ex}{0.5ex plus .2ex}{\normalsize\bf\raggedright}} +\def\paragraph{\@startsection{paragraph}{4}{\z@}{1.5ex plus + 0.5ex minus .2ex}{-1em}{\normalsize\bf}} +\def\subparagraph{\@startsection{subparagraph}{5}{\parindent}{1.5ex plus + 0.5ex minus .2ex}{-1em}{\normalsize\bf}} + +% Footnotes +\footnotesep 6.65pt % +\skip\footins 9pt plus 4pt minus 2pt +\def\footnoterule{\kern-3pt \hrule width 5pc \kern 2.6pt } +\setcounter{footnote}{0} + +% Lists and paragraphs +\parindent 1em +\topsep 4pt plus 1pt minus 2pt +\partopsep 1pt plus 0.5pt minus 0.5pt +\itemsep 2pt plus 1pt minus 0.5pt +\parsep 2pt plus 1pt minus 0.5pt + +\leftmargin 2em \leftmargini\leftmargin \leftmarginii 2em +\leftmarginiii 1.5em \leftmarginiv 1.0em \leftmarginv .5em \leftmarginvi .5em +\labelwidth\leftmargini\advance\labelwidth-\labelsep \labelsep 5pt + +\def\@listi{\leftmargin\leftmargini} +\def\@listii{\leftmargin\leftmarginii + \labelwidth\leftmarginii\advance\labelwidth-\labelsep + \topsep 2pt plus 1pt minus 0.5pt + \parsep 1pt plus 0.5pt minus 0.5pt + \itemsep \parsep} +\def\@listiii{\leftmargin\leftmarginiii + \labelwidth\leftmarginiii\advance\labelwidth-\labelsep + \topsep 1pt plus 0.5pt minus 0.5pt + \parsep \z@ \partopsep 0.5pt plus 0pt minus 0.5pt + \itemsep \topsep} +\def\@listiv{\leftmargin\leftmarginiv + \labelwidth\leftmarginiv\advance\labelwidth-\labelsep} +\def\@listv{\leftmargin\leftmarginv + \labelwidth\leftmarginv\advance\labelwidth-\labelsep} +\def\@listvi{\leftmargin\leftmarginvi + \labelwidth\leftmarginvi\advance\labelwidth-\labelsep} + +\abovedisplayskip 7pt plus2pt minus5pt% +\belowdisplayskip \abovedisplayskip +\abovedisplayshortskip 0pt plus3pt% +\belowdisplayshortskip 4pt plus3pt minus3pt% + +% Less leading in most fonts (due to the narrow columns) +% The choices were between 1-pt and 1.5-pt leading +%\def\@normalsize{\@setsize\normalsize{11pt}\xpt\@xpt} +%\def\small{\@setsize\small{10pt}\ixpt\@ixpt} +%\def\footnotesize{\@setsize\footnotesize{10pt}\ixpt\@ixpt} +%\def\scriptsize{\@setsize\scriptsize{8pt}\viipt\@viipt} +%\def\tiny{\@setsize\tiny{7pt}\vipt\@vipt} +%\def\large{\@setsize\large{14pt}\xiipt\@xiipt} +%\def\Large{\@setsize\Large{16pt}\xivpt\@xivpt} +%\def\LARGE{\@setsize\LARGE{20pt}\xviipt\@xviipt} +%\def\huge{\@setsize\huge{23pt}\xxpt\@xxpt} +%\def\Huge{\@setsize\Huge{28pt}\xxvpt\@xxvpt} + +\let\@@makecaption\@makecaption +\renewcommand{\@makecaption}[1]{\@@makecaption{\small #1}} + +\newcommand{\Thanks}[1]{\thanks{\ #1}} \ No newline at end of file diff --git a/papers/2011_emnlp_unsup_impact/acl-hlt2011.tex b/papers/2011_emnlp_unsup_impact/acl-hlt2011.tex new file mode 100644 index 00000000..556be4da --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/acl-hlt2011.tex @@ -0,0 +1,323 @@ +% +% File acl-hlt2011.tex +% +% Contact: gdzhou@suda.edu.cn +%% +%% Based on the style files for ACL2008 by Joakim Nivre and Noah Smith +%% and that of ACL2010 by Jing-Shin Chang and Philipp Koehn + + +\documentclass[11pt]{article} +\usepackage{acl-hlt2011} +\usepackage{times} +\usepackage{latexsym} +\usepackage{amsmath} +\usepackage{multirow} +\usepackage{url} +\DeclareMathOperator*{\argmax}{arg\,max} +\setlength\titlebox{6.5cm} % Expanding the titlebox + +\title{Instructions for ACL-HLT-2011 Proceedings} + +\author{First Author \\ + Affiliation / Address line 1 \\ + Affiliation / Address line 2 \\ + Affiliation / Address line 3 \\ + {\tt email@domain} \\\And + Second Author \\ + Affiliation / Address line 1 \\ + Affiliation / Address line 2 \\ + Affiliation / Address line 3 \\ + {\tt email@domain} \\} + +\date{} + +\begin{document} +\maketitle +\begin{abstract} + This document contains the instructions for preparing a camera-ready manuscript for the proceedings of ACL-HLT-2011. The document itself conforms to its own specifications, and is therefore an example of what your manuscript should look like. These instructions should be used for both papers submitted for review and for final versions of accepted papers. Authors are asked to conform to all the directions reported in this document. +\end{abstract} + +\section{Credits} + +This document has been adapted from the instructions for earlier ACL proceedings, including those for ACL-2008 by Johanna D. Moore, Simone Teufel, James Allan, and Sadaoki Furui, those for ACL-2005 by Hwee Tou Ng and Kemal Oflazer, those for ACL-2002 by Eugene Charniak and Dekang Lin, and earlier ACL and EACL formats. Those versions were written by several people, including John Chen, Henry S. Thompson and Donald Walker. Additional elements were taken from the formatting instructions of the {\em International Joint Conference on Artificial Intelligence}. + +\section{Introduction} + +The following instructions are directed to authors of papers submitted to ACL-HLT-2011 or accepted for publication in its proceedings. All authors are required to adhere to these specifications. Authors are required to provide a Portable Document Format (PDF) +% das: removed reference to PostScript +% and PostScript +version of their papers. \textbf{The proceedings will be printed on US-Letter paper}. Authors from countries in which access to word-processing systems is limited should contact the publication chair Guodong Zhou ({\tt gdzhou@suda.edu.cn}) as soon as possible. + + +\section{General Instructions} + +Manuscripts must be in two-column format. Exceptions to the two-column format include the title, authors' names and complete addresses, which must be centered at the top of the first page, and any full-width figures or tables (see the guidelines in Subsection~\ref{ssec:first}). {\bf Type single-spaced}. Start all pages directly under the top margin. See the guide-lines later regarding formatting the first page. + +The maximum length of a manuscript is eight (8) pages for the main conference, printed single-sided, plus two (2) pages for references (see Section~\ref{sec:length} for additional information on the maximum number of pages). Do not number the pages. + +\subsection{Electronically-available resources} + +ACL-HLT-2011 provides this description in \LaTeX2e (acl-hlt2011.tex) and PDF format (acl-hlt2011.pdf), along with the LATEX2e style file used to format it (acl-hlt2011.sty) and an ACL bibliography style (acl.bst). These files are all available at \url{http://www.acl2011.org}. A Microsoft Word template file (acl-hlt2011.dot) is also available at the same URL. We strongly recommend the use of these style files, which have been appropriately tailored for the ACL-HLT-2011 proceedings. If you have an option, we recommend that you use the \LaTeX2e version. \textbf{If you will be using the Microsoft Word template, we suggest that you anonymize your source file so that the pdf produced does not retain your identity.} This can be done by removing any personal information from your source +document properties. + + +\subsection{Format of Electronic Manuscript} +\label{sect:pdf} + +For the production of the electronic manuscript you must use Adobe's +Portable Document Format (PDF). This format can be generated from +postscript files: on Linux/Unix systems, you can use {\tt ps2pdf} for this +purpose; under Microsoft Windows, you can use Adobe's Distiller, or +if you have {\tt cygwin} installed, you can use {\tt dvipdf} or +{\tt ps2pdf}. Note +that some word processing programs generate PDF which may not include +all the necessary fonts (esp. tree diagrams, symbols). When you print +or create the PDF file, there is usually an option in your printer +setup to include none, all or just non-standard fonts. Please make +sure that you select the option of including ALL the fonts. {\em Before sending it, test your PDF by printing it from a computer different from the one where it was created}. Moreover, +some word processor may generate very large postscript/PDF files, +where each page is rendered as an image. Such images may reproduce +poorly. In this case, try alternative ways to obtain the postscript +and/or PDF. One way on some systems is to install a driver for a +postscript printer, send your document to the printer specifying +``Output to a file'', then convert the file to PDF. + +Additionally, it is of utmost importance to specify the {\bf US-Letter format} (8.5in $\times$ 11in) when formatting the paper. When working with {\tt dvips}, for instance, one should specify {\tt -t letter}. + +Print-outs of the PDF file on US-Letter paper should be identical to the +hardcopy version. If you cannot meet the above requirements about the +production of your electronic submission, please contact the +publication chair above as soon as possible. + + +\subsection{Layout} +\label{ssec:layout} + +Format manuscripts two columns to a page, in the manner these +instructions are formatted. The exact dimensions for a page on US-letter +paper are: + +\begin{itemize} +\item Left and right margins: 1in +\item Top margin:1in +\item Bottom margin: 1in +\item Column width: 3.15in +\item Column height: 9in +\item Gap between columns: 0.2in +\end{itemize} + +\noindent Papers should not be submitted on any other paper size. If you cannot meet the above requirements about the production of your electronic submission, please contact the publication chair above as soon as possible. + +\subsection{Fonts} + +For reasons of uniformity, Adobe's {\bf Times Roman} font should be +used. In \LaTeX2e{} this is accomplished by putting + +\begin{quote} +\begin{verbatim} +\usepackage{times} +\usepackage{latexsym} +\end{verbatim} +\end{quote} +in the preamble. If Times Roman is unavailable, use {\bf Computer + Modern Roman} (\LaTeX2e{}'s default). Note that the latter is about + 10\% less dense than Adobe's Times Roman font. + + +\begin{table}[h] +\begin{center} +\begin{tabular}{|l|rl|} +\hline \bf Type of Text & \bf Font Size & \bf Style \\ \hline +paper title & 15 pt & bold \\ +author names & 12 pt & bold \\ +author affiliation & 12 pt & \\ +the word ``Abstract'' & 12 pt & bold \\ +section titles & 12 pt & bold \\ +document text & 11 pt &\\ +captions & 11 pt & \\ +abstract text & 10 pt & \\ +bibliography & 10 pt & \\ +footnotes & 9 pt & \\ +\hline +\end{tabular} +\end{center} +\caption{\label{font-table} Font guide. } +\end{table} + +\subsection{The First Page} +\label{ssec:first} + +Center the title, author's name(s) and affiliation(s) across both +columns. Do not use footnotes for affiliations. Do not include the +paper ID number assigned during the submission process. +Use the two-column format only when you begin the abstract. + +{\bf Title}: Place the title centered at the top of the first page, in +a 15 point bold font. (For a complete guide to font sizes and styles, see Table~\ref{font-table}.) +Long title should be typed on two lines without +a blank line intervening. Approximately, put the title at 1in from the +top of the page, followed by a blank line, then the author's names(s), +and the affiliation on the following line. Do not use only initials +for given names (middle initials are allowed). Do not format surnames +in all capitals (e.g., ``Zhou,'' not ``ZHOU''). The affiliation should +contain the author's complete address, and if possible an electronic +mail address. Leave about 0.75in between the affiliation and the body +of the first page. The title, author names and addresses should be completely identical to those entered to the electronic paper submission website in order to maintain the consistency of author information among all publications of the conference. + +{\bf Abstract}: Type the abstract at the beginning of the first +column. The width of the abstract text should be smaller than the +width of the columns for the text in the body of the paper by about +0.25in on each side. Center the word {\bf Abstract} in a 12 point +bold font above the body of the abstract. The abstract should be a +concise summary of the general thesis and conclusions of the paper. +It should be no longer than 200 words. The abstract text should be in 10 point font. + +{\bf Text}: Begin typing the main body of the text immediately after +the abstract, observing the two-column format as shown in +the present document. Do not include page numbers. + +{\bf Indent} when starting a new paragraph. For reasons of uniformity, +use Adobe's {\bf Times Roman} fonts, with 11 points for text and +subsection headings, 12 points for section headings and 15 points for +the title. If Times Roman is unavailable, use {\bf Computer Modern + Roman} (\LaTeX2e's default; see section \ref{sect:pdf} above). +Note that the latter is about 10\% less dense than Adobe's Times Roman +font. + +\subsection{Sections} + +{\bf Headings}: Type and label section and subsection headings in the +style shown on the present document. Use numbered sections (Arabic +numerals) in order to facilitate cross references. Number subsections +with the section number and the subsection number separated by a dot, +in Arabic numerals. Do not number subsubsections. + +{\bf Citations}: Citations within the text appear +in parentheses as~\cite{Gusfield:97} or, if the author's name appears in +the text itself, as Gusfield~\shortcite{Gusfield:97}. Append lowercase letters to the year in cases of ambiguities. Treat double authors as in~\cite{Aho:72}, but write as in~\cite{Chandra:81} when more than two authors are involved. Collapse multiple citations as in~\cite{Gusfield:97,Aho:72}. Also refrain from using full citations as sentence constituents. We suggest that instead of +\begin{quote} + ``\cite{Gusfield:97} showed that ...'' +\end{quote} +you use +\begin{quote} +``Gusfield \shortcite{Gusfield:97} showed that ...'' +\end{quote} + +If you are using the provided \LaTeX{} and Bib\TeX{} style files, you +can use the command \verb|\newcite| to get ``author (year)'' citations. + +As reviewing will be double-blind, the submitted version of the papers should not include the +authors' names and affiliations. Furthermore, self-references that +reveal the author's identity, e.g., +\begin{quote} +``We previously showed \cite{Gusfield:97} ...'' +\end{quote} +should be avoided. Instead, use citations such as +\begin{quote} +``Gusfield \shortcite{Gusfield:97} +previously showed ... '' +\end{quote} + +Please do not use anonymous +citations and do not include acknowledgements when submitting your papers. Papers that do not conform +to these requirements may be rejected without review. + +\textbf{References}: Gather the full set of references together under +the heading {\bf References}; place the section before any Appendices, +unless they contain references. Arrange the references alphabetically +by first author, rather than by order of occurrence in the text. +Provide as complete a citation as possible, using a consistent format, +such as the one for {\em Computational Linguistics\/} or the one in the +{\em Publication Manual of the American +Psychological Association\/}~\cite{APA:83}. Use of full names for +authors rather than initials is preferred. A list of abbreviations +for common computer science journals can be found in the ACM +{\em Computing Reviews\/}~\cite{ACM:83}. + +The \LaTeX{} and Bib\TeX{} style files provided roughly fit the +American Psychological Association format, allowing regular citations, +short citations and multiple citations as described above. + +{\bf Appendices}: Appendices, if any, directly follow the text and the +references (but see above). Letter them in sequence and provide an +informative title: {\bf Appendix A. Title of Appendix}. + +\textbf{Acknowledgment} sections should go as a last section immediately +before the references. Do not number the acknowledgement section. + +\subsection{Footnotes} + +{\bf Footnotes}: Put footnotes at the bottom of the page. They may +be numbered or referred to by asterisks or other +symbols.\footnote{This is how a footnote should appear.} Footnotes +should be separated from the text by a line.\footnote{Note the +line separating the footnotes from the text.} Footnotes should be in 9 point font. + +\subsection{Graphics} + +{\bf Illustrations}: Place figures, tables, and photographs in the +paper near where they are first discussed, rather than at the end, if +possible. Wide illustrations may run across both columns and should be placed at +the top of a page. Color illustrations are discouraged, unless you have verified that +they will be understandable when printed in black ink. + +{\bf Captions}: Provide a caption for every illustration; number each one +sequentially in the form: ``Figure 1. Caption of the Figure.'' ``Table 1. +Caption of the Table.'' Type the captions of the figures and +tables below the body, using 10 point text. + +\section{Translation of non-English Terms} + +It is also advised to supplement non-English characters and terms +with appropriate transliterations and/or translations +since not all readers understand all such characters and terms. + +Inline transliteration or translation can be represented in +the order of: original-form transliteration ``translation''. + +\section{Length of Submission} +\label{sec:length} + +Long papers may consist of up to eight (8) pages of content (excluding references), and short papers may consists of up to four (4) pages of content (excluding references). Both long and short papers may include up to two (2) additional pages for references only. All illustrations, references, and appendices must be accommodated within these page limits, observing the formatting instructions given in the present document. Papers that do not conform to the specified length and formatting requirements are subject to be rejected without review. + + +\section*{Acknowledgments} + +Do not number the acknowledgment section. Do not include this section when submitting your paper for review. + +\begin{thebibliography}{} + +\bibitem[\protect\citename{Aho and Ullman}1972]{Aho:72} +Alfred~V. Aho and Jeffrey~D. Ullman. +\newblock 1972. +\newblock {\em The Theory of Parsing, Translation and Compiling}, volume~1. +\newblock Prentice-{Hall}, Englewood Cliffs, NJ. + +\bibitem[\protect\citename{{American Psychological Association}}1983]{APA:83} +{American Psychological Association}. +\newblock 1983. +\newblock {\em Publications Manual}. +\newblock American Psychological Association, Washington, DC. + +\bibitem[\protect\citename{{Association for Computing Machinery}}1983]{ACM:83} +{Association for Computing Machinery}. +\newblock 1983. +\newblock {\em Computing Reviews}, 24(11):503--512. + +\bibitem[\protect\citename{Chandra \bgroup et al.\egroup }1981]{Chandra:81} +Ashok~K. Chandra, Dexter~C. Kozen, and Larry~J. Stockmeyer. +\newblock 1981. +\newblock Alternation. +\newblock {\em Journal of the Association for Computing Machinery}, + 28(1):114--133. + +\bibitem[\protect\citename{Gusfield}1997]{Gusfield:97} +Dan Gusfield. +\newblock 1997. +\newblock {\em Algorithms on Strings, Trees and Sequences}. +\newblock Cambridge University Press, Cambridge, UK. + +\end{thebibliography} + +\end{document} diff --git a/papers/2011_emnlp_unsup_impact/acl.bst b/papers/2011_emnlp_unsup_impact/acl.bst new file mode 100644 index 00000000..b95ec040 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/acl.bst @@ -0,0 +1,1322 @@ + +% BibTeX `acl' style file for BibTeX version 0.99c, LaTeX version 2.09 +% This version was made by modifying `aaai-named' format based on the master +% file by Oren Patashnik (PATASHNIK@SCORE.STANFORD.EDU) + +% Copyright (C) 1985, all rights reserved. +% Modifications Copyright 1988, Peter F. Patel-Schneider +% Further modifictions by Stuart Shieber, 1991, and Fernando Pereira, 1992. +% Copying of this file is authorized only if either +% (1) you make absolutely no changes to your copy, including name, or +% (2) if you do make changes, you name it something other than +% btxbst.doc, plain.bst, unsrt.bst, alpha.bst, and abbrv.bst. +% This restriction helps ensure that all standard styles are identical. + +% There are undoubtably bugs in this style. If you make bug fixes, +% improvements, etc. please let me know. My e-mail address is: +% pfps@spar.slb.com + +% Citation format: [author-last-name, year] +% [author-last-name and author-last-name, year] +% [author-last-name {\em et al.}, year] +% +% Reference list ordering: alphabetical by author or whatever passes +% for author in the absence of one. +% +% This BibTeX style has support for short (year only) citations. This +% is done by having the citations actually look like +% \citename{name-info, }year +% The LaTeX style has to have the following +% \let\@internalcite\cite +% \def\cite{\def\citename##1{##1}\@internalcite} +% \def\shortcite{\def\citename##1{}\@internalcite} +% \def\@biblabel#1{\def\citename##1{##1}[#1]\hfill} +% which makes \shortcite the macro for short citations. + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% Changes made by SMS for thesis style +% no emphasis on "et al." +% "Ph.D." includes periods (not "PhD") +% moved year to immediately after author's name +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +ENTRY + { address + author + booktitle + chapter + edition + editor + howpublished + institution + journal + key + month + note + number + organization + pages + publisher + school + series + title + type + volume + year + } + {} + { label extra.label sort.label } + +INTEGERS { output.state before.all mid.sentence after.sentence after.block } + +FUNCTION {init.state.consts} +{ #0 'before.all := + #1 'mid.sentence := + #2 'after.sentence := + #3 'after.block := +} + +STRINGS { s t } + +FUNCTION {output.nonnull} +{ 's := + output.state mid.sentence = + { ", " * write$ } + { output.state after.block = + { add.period$ write$ + newline$ + "\newblock " write$ + } + { output.state before.all = + 'write$ + { add.period$ " " * write$ } + if$ + } + if$ + mid.sentence 'output.state := + } + if$ + s +} + +FUNCTION {output} +{ duplicate$ empty$ + 'pop$ + 'output.nonnull + if$ +} + +FUNCTION {output.check} +{ 't := + duplicate$ empty$ + { pop$ "empty " t * " in " * cite$ * warning$ } + 'output.nonnull + if$ +} + +FUNCTION {output.bibitem} +{ newline$ + + "\bibitem[" write$ + label write$ + "]{" write$ + + cite$ write$ + "}" write$ + newline$ + "" + before.all 'output.state := +} + +FUNCTION {fin.entry} +{ add.period$ + write$ + newline$ +} + +FUNCTION {new.block} +{ output.state before.all = + 'skip$ + { after.block 'output.state := } + if$ +} + +FUNCTION {new.sentence} +{ output.state after.block = + 'skip$ + { output.state before.all = + 'skip$ + { after.sentence 'output.state := } + if$ + } + if$ +} + +FUNCTION {not} +{ { #0 } + { #1 } + if$ +} + +FUNCTION {and} +{ 'skip$ + { pop$ #0 } + if$ +} + +FUNCTION {or} +{ { pop$ #1 } + 'skip$ + if$ +} + +FUNCTION {new.block.checka} +{ empty$ + 'skip$ + 'new.block + if$ +} + +FUNCTION {new.block.checkb} +{ empty$ + swap$ empty$ + and + 'skip$ + 'new.block + if$ +} + +FUNCTION {new.sentence.checka} +{ empty$ + 'skip$ + 'new.sentence + if$ +} + +FUNCTION {new.sentence.checkb} +{ empty$ + swap$ empty$ + and + 'skip$ + 'new.sentence + if$ +} + +FUNCTION {field.or.null} +{ duplicate$ empty$ + { pop$ "" } + 'skip$ + if$ +} + +FUNCTION {emphasize} +{ duplicate$ empty$ + { pop$ "" } + { "{\em " swap$ * "}" * } + if$ +} + +INTEGERS { nameptr namesleft numnames } + +FUNCTION {format.names} +{ 's := + #1 'nameptr := + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + + { s nameptr "{ff~}{vv~}{ll}{, jj}" format.name$ 't := + + nameptr #1 > + { namesleft #1 > + { ", " * t * } + { numnames #2 > + { "," * } + 'skip$ + if$ + t "others" = + { " et~al." * } + { " and " * t * } + if$ + } + if$ + } + 't + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {format.authors} +{ author empty$ + { "" } + { author format.names } + if$ +} + +FUNCTION {format.editors} +{ editor empty$ + { "" } + { editor format.names + editor num.names$ #1 > + { ", editors" * } + { ", editor" * } + if$ + } + if$ +} + +FUNCTION {format.title} +{ title empty$ + { "" } + + { title "t" change.case$ } + + if$ +} + +FUNCTION {n.dashify} +{ 't := + "" + { t empty$ not } + { t #1 #1 substring$ "-" = + { t #1 #2 substring$ "--" = not + { "--" * + t #2 global.max$ substring$ 't := + } + { { t #1 #1 substring$ "-" = } + { "-" * + t #2 global.max$ substring$ 't := + } + while$ + } + if$ + } + { t #1 #1 substring$ * + t #2 global.max$ substring$ 't := + } + if$ + } + while$ +} + +FUNCTION {format.date} +{ year empty$ + { month empty$ + { "" } + { "there's a month but no year in " cite$ * warning$ + month + } + if$ + } + { month empty$ + { "" } + { month } + if$ + } + if$ +} + +FUNCTION {format.btitle} +{ title emphasize +} + +FUNCTION {tie.or.space.connect} +{ duplicate$ text.length$ #3 < + { "~" } + { " " } + if$ + swap$ * * +} + +FUNCTION {either.or.check} +{ empty$ + 'pop$ + { "can't use both " swap$ * " fields in " * cite$ * warning$ } + if$ +} + +FUNCTION {format.bvolume} +{ volume empty$ + { "" } + { "volume" volume tie.or.space.connect + series empty$ + 'skip$ + { " of " * series emphasize * } + if$ + "volume and number" number either.or.check + } + if$ +} + +FUNCTION {format.number.series} +{ volume empty$ + { number empty$ + { series field.or.null } + { output.state mid.sentence = + { "number" } + { "Number" } + if$ + number tie.or.space.connect + series empty$ + { "there's a number but no series in " cite$ * warning$ } + { " in " * series * } + if$ + } + if$ + } + { "" } + if$ +} + +FUNCTION {format.edition} +{ edition empty$ + { "" } + { output.state mid.sentence = + { edition "l" change.case$ " edition" * } + { edition "t" change.case$ " edition" * } + if$ + } + if$ +} + +INTEGERS { multiresult } + +FUNCTION {multi.page.check} +{ 't := + #0 'multiresult := + { multiresult not + t empty$ not + and + } + { t #1 #1 substring$ + duplicate$ "-" = + swap$ duplicate$ "," = + swap$ "+" = + or or + { #1 'multiresult := } + { t #2 global.max$ substring$ 't := } + if$ + } + while$ + multiresult +} + +FUNCTION {format.pages} +{ pages empty$ + { "" } + { pages multi.page.check + { "pages" pages n.dashify tie.or.space.connect } + { "page" pages tie.or.space.connect } + if$ + } + if$ +} + +FUNCTION {format.year.label} +{ year extra.label * +} + +FUNCTION {format.vol.num.pages} +{ volume field.or.null + number empty$ + 'skip$ + { "(" number * ")" * * + volume empty$ + { "there's a number but no volume in " cite$ * warning$ } + 'skip$ + if$ + } + if$ + pages empty$ + 'skip$ + { duplicate$ empty$ + { pop$ format.pages } + { ":" * pages n.dashify * } + if$ + } + if$ +} + +FUNCTION {format.chapter.pages} +{ chapter empty$ + 'format.pages + { type empty$ + { "chapter" } + { type "l" change.case$ } + if$ + chapter tie.or.space.connect + pages empty$ + 'skip$ + { ", " * format.pages * } + if$ + } + if$ +} + +FUNCTION {format.in.ed.booktitle} +{ booktitle empty$ + { "" } + { editor empty$ + { "In " booktitle emphasize * } + { "In " format.editors * ", " * booktitle emphasize * } + if$ + } + if$ +} + +FUNCTION {empty.misc.check} +{ author empty$ title empty$ howpublished empty$ + month empty$ year empty$ note empty$ + and and and and and + + key empty$ not and + + { "all relevant fields are empty in " cite$ * warning$ } + 'skip$ + if$ +} + +FUNCTION {format.thesis.type} +{ type empty$ + 'skip$ + { pop$ + type "t" change.case$ + } + if$ +} + +FUNCTION {format.tr.number} +{ type empty$ + { "Technical Report" } + 'type + if$ + number empty$ + { "t" change.case$ } + { number tie.or.space.connect } + if$ +} + +FUNCTION {format.article.crossref} +{ key empty$ + { journal empty$ + { "need key or journal for " cite$ * " to crossref " * crossref * + warning$ + "" + } + { "In {\em " journal * "\/}" * } + if$ + } + { "In " key * } + if$ + " \cite{" * crossref * "}" * +} + +FUNCTION {format.crossref.editor} +{ editor #1 "{vv~}{ll}" format.name$ + editor num.names$ duplicate$ + #2 > + { pop$ " et~al." * } + { #2 < + 'skip$ + { editor #2 "{ff }{vv }{ll}{ jj}" format.name$ "others" = + { " et~al." * } + { " and " * editor #2 "{vv~}{ll}" format.name$ * } + if$ + } + if$ + } + if$ +} + +FUNCTION {format.book.crossref} +{ volume empty$ + { "empty volume in " cite$ * "'s crossref of " * crossref * warning$ + "In " + } + { "Volume" volume tie.or.space.connect + " of " * + } + if$ + editor empty$ + editor field.or.null author field.or.null = + or + { key empty$ + { series empty$ + { "need editor, key, or series for " cite$ * " to crossref " * + crossref * warning$ + "" * + } + { "{\em " * series * "\/}" * } + if$ + } + { key * } + if$ + } + { format.crossref.editor * } + if$ + " \cite{" * crossref * "}" * +} + +FUNCTION {format.incoll.inproc.crossref} +{ editor empty$ + editor field.or.null author field.or.null = + or + { key empty$ + { booktitle empty$ + { "need editor, key, or booktitle for " cite$ * " to crossref " * + crossref * warning$ + "" + } + { "In {\em " booktitle * "\/}" * } + if$ + } + { "In " key * } + if$ + } + { "In " format.crossref.editor * } + if$ + " \cite{" * crossref * "}" * +} + +FUNCTION {article} +{ output.bibitem + format.authors "author" output.check + new.block + format.year.label "year" output.check + new.block + format.title "title" output.check + new.block + crossref missing$ + { journal emphasize "journal" output.check + format.vol.num.pages output + format.date output + } + { format.article.crossref output.nonnull + format.pages output + } + if$ + new.block + note output + fin.entry +} + +FUNCTION {book} +{ output.bibitem + author empty$ + { format.editors "author and editor" output.check } + { format.authors output.nonnull + crossref missing$ + { "author and editor" editor either.or.check } + 'skip$ + if$ + } + if$ + new.block + format.year.label "year" output.check + new.block + format.btitle "title" output.check + crossref missing$ + { format.bvolume output + new.block + format.number.series output + new.sentence + publisher "publisher" output.check + address output + } + { new.block + format.book.crossref output.nonnull + } + if$ + format.edition output + format.date output + new.block + note output + fin.entry +} + +FUNCTION {booklet} +{ output.bibitem + format.authors output + new.block + format.year.label "year" output.check + new.block + format.title "title" output.check + howpublished address new.block.checkb + howpublished output + address output + format.date output + new.block + note output + fin.entry +} + +FUNCTION {inbook} +{ output.bibitem + author empty$ + { format.editors "author and editor" output.check } + { format.authors output.nonnull + crossref missing$ + { "author and editor" editor either.or.check } + 'skip$ + if$ + } + if$ + format.year.label "year" output.check + new.block + new.block + format.btitle "title" output.check + crossref missing$ + { format.bvolume output + format.chapter.pages "chapter and pages" output.check + new.block + format.number.series output + new.sentence + publisher "publisher" output.check + address output + } + { format.chapter.pages "chapter and pages" output.check + new.block + format.book.crossref output.nonnull + } + if$ + format.edition output + format.date output + new.block + note output + fin.entry +} + +FUNCTION {incollection} +{ output.bibitem + format.authors "author" output.check + new.block + format.year.label "year" output.check + new.block + format.title "title" output.check + new.block + crossref missing$ + { format.in.ed.booktitle "booktitle" output.check + format.bvolume output + format.number.series output + format.chapter.pages output + new.sentence + publisher "publisher" output.check + address output + format.edition output + format.date output + } + { format.incoll.inproc.crossref output.nonnull + format.chapter.pages output + } + if$ + new.block + note output + fin.entry +} + +FUNCTION {inproceedings} +{ output.bibitem + format.authors "author" output.check + new.block + format.year.label "year" output.check + new.block + format.title "title" output.check + new.block + crossref missing$ + { format.in.ed.booktitle "booktitle" output.check + format.bvolume output + format.number.series output + format.pages output + address empty$ + { organization publisher new.sentence.checkb + organization output + publisher output + format.date output + } + { address output.nonnull + format.date output + new.sentence + organization output + publisher output + } + if$ + } + { format.incoll.inproc.crossref output.nonnull + format.pages output + } + if$ + new.block + note output + fin.entry +} + +FUNCTION {conference} { inproceedings } + +FUNCTION {manual} +{ output.bibitem + author empty$ + { organization empty$ + 'skip$ + { organization output.nonnull + address output + } + if$ + } + { format.authors output.nonnull } + if$ + format.year.label "year" output.check + new.block + new.block + format.btitle "title" output.check + author empty$ + { organization empty$ + { address new.block.checka + address output + } + 'skip$ + if$ + } + { organization address new.block.checkb + organization output + address output + } + if$ + format.edition output + format.date output + new.block + note output + fin.entry +} + +FUNCTION {mastersthesis} +{ output.bibitem + format.authors "author" output.check + new.block + format.year.label "year" output.check + new.block + format.title "title" output.check + new.block + "Master's thesis" format.thesis.type output.nonnull + school "school" output.check + address output + format.date output + new.block + note output + fin.entry +} + +FUNCTION {misc} +{ output.bibitem + format.authors output + new.block + format.year.label output + new.block + title howpublished new.block.checkb + format.title output + howpublished new.block.checka + howpublished output + format.date output + new.block + note output + fin.entry + empty.misc.check +} + +FUNCTION {phdthesis} +{ output.bibitem + format.authors "author" output.check + new.block + format.year.label "year" output.check + new.block + format.btitle "title" output.check + new.block + "{Ph.D.} thesis" format.thesis.type output.nonnull + school "school" output.check + address output + format.date output + new.block + note output + fin.entry +} + +FUNCTION {proceedings} +{ output.bibitem + editor empty$ + { organization output } + { format.editors output.nonnull } + if$ + new.block + format.year.label "year" output.check + new.block + format.btitle "title" output.check + format.bvolume output + format.number.series output + address empty$ + { editor empty$ + { publisher new.sentence.checka } + { organization publisher new.sentence.checkb + organization output + } + if$ + publisher output + format.date output + } + { address output.nonnull + format.date output + new.sentence + editor empty$ + 'skip$ + { organization output } + if$ + publisher output + } + if$ + new.block + note output + fin.entry +} + +FUNCTION {techreport} +{ output.bibitem + format.authors "author" output.check + new.block + format.year.label "year" output.check + new.block + format.title "title" output.check + new.block + format.tr.number output.nonnull + institution "institution" output.check + address output + format.date output + new.block + note output + fin.entry +} + +FUNCTION {unpublished} +{ output.bibitem + format.authors "author" output.check + new.block + format.year.label "year" output.check + new.block + format.title "title" output.check + new.block + note "note" output.check + format.date output + fin.entry +} + +FUNCTION {default.type} { misc } + +MACRO {jan} {"January"} + +MACRO {feb} {"February"} + +MACRO {mar} {"March"} + +MACRO {apr} {"April"} + +MACRO {may} {"May"} + +MACRO {jun} {"June"} + +MACRO {jul} {"July"} + +MACRO {aug} {"August"} + +MACRO {sep} {"September"} + +MACRO {oct} {"October"} + +MACRO {nov} {"November"} + +MACRO {dec} {"December"} + +MACRO {acmcs} {"ACM Computing Surveys"} + +MACRO {acta} {"Acta Informatica"} + +MACRO {cacm} {"Communications of the ACM"} + +MACRO {ibmjrd} {"IBM Journal of Research and Development"} + +MACRO {ibmsj} {"IBM Systems Journal"} + +MACRO {ieeese} {"IEEE Transactions on Software Engineering"} + +MACRO {ieeetc} {"IEEE Transactions on Computers"} + +MACRO {ieeetcad} + {"IEEE Transactions on Computer-Aided Design of Integrated Circuits"} + +MACRO {ipl} {"Information Processing Letters"} + +MACRO {jacm} {"Journal of the ACM"} + +MACRO {jcss} {"Journal of Computer and System Sciences"} + +MACRO {scp} {"Science of Computer Programming"} + +MACRO {sicomp} {"SIAM Journal on Computing"} + +MACRO {tocs} {"ACM Transactions on Computer Systems"} + +MACRO {tods} {"ACM Transactions on Database Systems"} + +MACRO {tog} {"ACM Transactions on Graphics"} + +MACRO {toms} {"ACM Transactions on Mathematical Software"} + +MACRO {toois} {"ACM Transactions on Office Information Systems"} + +MACRO {toplas} {"ACM Transactions on Programming Languages and Systems"} + +MACRO {tcs} {"Theoretical Computer Science"} + +READ + +FUNCTION {sortify} +{ purify$ + "l" change.case$ +} + +INTEGERS { len } + +FUNCTION {chop.word} +{ 's := + 'len := + s #1 len substring$ = + { s len #1 + global.max$ substring$ } + 's + if$ +} + +INTEGERS { et.al.char.used } + +FUNCTION {initialize.et.al.char.used} +{ #0 'et.al.char.used := +} + +EXECUTE {initialize.et.al.char.used} + +FUNCTION {format.lab.names} +{ 's := + s num.names$ 'numnames := + + numnames #1 = + { s #1 "{vv }{ll}" format.name$ } + { numnames #2 = + { s #1 "{vv }{ll }and " format.name$ s #2 "{vv }{ll}" format.name$ * + } + { s #1 "{vv }{ll }\bgroup et al.\egroup " format.name$ } + if$ + } + if$ + +} + +FUNCTION {author.key.label} +{ author empty$ + { key empty$ + + { cite$ #1 #3 substring$ } + + { key #3 text.prefix$ } + if$ + } + { author format.lab.names } + if$ +} + +FUNCTION {author.editor.key.label} +{ author empty$ + { editor empty$ + { key empty$ + + { cite$ #1 #3 substring$ } + + { key #3 text.prefix$ } + if$ + } + { editor format.lab.names } + if$ + } + { author format.lab.names } + if$ +} + +FUNCTION {author.key.organization.label} +{ author empty$ + { key empty$ + { organization empty$ + + { cite$ #1 #3 substring$ } + + { "The " #4 organization chop.word #3 text.prefix$ } + if$ + } + { key #3 text.prefix$ } + if$ + } + { author format.lab.names } + if$ +} + +FUNCTION {editor.key.organization.label} +{ editor empty$ + { key empty$ + { organization empty$ + + { cite$ #1 #3 substring$ } + + { "The " #4 organization chop.word #3 text.prefix$ } + if$ + } + { key #3 text.prefix$ } + if$ + } + { editor format.lab.names } + if$ +} + +FUNCTION {calc.label} +{ type$ "book" = + type$ "inbook" = + or + 'author.editor.key.label + { type$ "proceedings" = + 'editor.key.organization.label + { type$ "manual" = + 'author.key.organization.label + 'author.key.label + if$ + } + if$ + } + if$ + duplicate$ + + "\protect\citename{" swap$ * "}" * + year field.or.null purify$ * + 'label := + year field.or.null purify$ * + + sortify 'sort.label := +} + +FUNCTION {sort.format.names} +{ 's := + #1 'nameptr := + "" + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + { nameptr #1 > + { " " * } + 'skip$ + if$ + + s nameptr "{vv{ } }{ll{ }}{ ff{ }}{ jj{ }}" format.name$ 't := + + nameptr numnames = t "others" = and + { "et al" * } + { t sortify * } + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {sort.format.title} +{ 't := + "A " #2 + "An " #3 + "The " #4 t chop.word + chop.word + chop.word + sortify + #1 global.max$ substring$ +} + +FUNCTION {author.sort} +{ author empty$ + { key empty$ + { "to sort, need author or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { author sort.format.names } + if$ +} + +FUNCTION {author.editor.sort} +{ author empty$ + { editor empty$ + { key empty$ + { "to sort, need author, editor, or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { editor sort.format.names } + if$ + } + { author sort.format.names } + if$ +} + +FUNCTION {author.organization.sort} +{ author empty$ + { organization empty$ + { key empty$ + { "to sort, need author, organization, or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { "The " #4 organization chop.word sortify } + if$ + } + { author sort.format.names } + if$ +} + +FUNCTION {editor.organization.sort} +{ editor empty$ + { organization empty$ + { key empty$ + { "to sort, need editor, organization, or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { "The " #4 organization chop.word sortify } + if$ + } + { editor sort.format.names } + if$ +} + +FUNCTION {presort} + +{ calc.label + sort.label + " " + * + type$ "book" = + + type$ "inbook" = + or + 'author.editor.sort + { type$ "proceedings" = + 'editor.organization.sort + { type$ "manual" = + 'author.organization.sort + 'author.sort + if$ + } + if$ + } + if$ + + * + + " " + * + year field.or.null sortify + * + " " + * + title field.or.null + sort.format.title + * + #1 entry.max$ substring$ + 'sort.key$ := +} + +ITERATE {presort} + +SORT + +STRINGS { longest.label last.sort.label next.extra } + +INTEGERS { longest.label.width last.extra.num } + +FUNCTION {initialize.longest.label} +{ "" 'longest.label := + #0 int.to.chr$ 'last.sort.label := + "" 'next.extra := + #0 'longest.label.width := + #0 'last.extra.num := +} + +FUNCTION {forward.pass} +{ last.sort.label sort.label = + { last.extra.num #1 + 'last.extra.num := + last.extra.num int.to.chr$ 'extra.label := + } + { "a" chr.to.int$ 'last.extra.num := + "" 'extra.label := + sort.label 'last.sort.label := + } + if$ +} + +FUNCTION {reverse.pass} +{ next.extra "b" = + { "a" 'extra.label := } + 'skip$ + if$ + label extra.label * 'label := + label width$ longest.label.width > + { label 'longest.label := + label width$ 'longest.label.width := + } + 'skip$ + if$ + extra.label 'next.extra := +} + +EXECUTE {initialize.longest.label} + +ITERATE {forward.pass} + +REVERSE {reverse.pass} + +FUNCTION {begin.bib} + +{ et.al.char.used + { "\newcommand{\etalchar}[1]{$^{#1}$}" write$ newline$ } + 'skip$ + if$ + preamble$ empty$ + + 'skip$ + { preamble$ write$ newline$ } + if$ + + "\begin{thebibliography}{" "}" * write$ newline$ + +} + +EXECUTE {begin.bib} + +EXECUTE {init.state.consts} + +ITERATE {call.type$} + +FUNCTION {end.bib} +{ newline$ + "\end{thebibliography}" write$ newline$ +} + +EXECUTE {end.bib} + diff --git a/papers/2011_emnlp_unsup_impact/code/plots/co-25-plots.all.p b/papers/2011_emnlp_unsup_impact/code/plots/co-25-plots.all.p new file mode 100644 index 00000000..48069cf2 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/co-25-plots.all.p @@ -0,0 +1,103 @@ +set term postscript eps enhanced color lw 3 "Helvetica" 28 +set output 'semEval-2010-dv-wc-wordsi-25-stkm-test.key.eps' +#set terminal png transparent nocrop enhanced font arial 8 size 500,350 +#set output 'semEval-2010-dv-wc-wordsi-25-stkm-test.key.png' + +#set style histogram #clustered gap 1 +#set style fill solid border 0 +set pointsize 2 + +#binwidth=1 +#set boxwidth binwidth + +set xrange [0.01 : .32] + +set ylabel "Frequency of Sense Confusion" +set xlabel "Ontonote Sense Similarity" + +plot 'semEval-2010-dv-wc-wordsi-25-stkm-test.key.avg.actual' using 1:2 title 'Actual (avg)' with linespoints , \ + 'semEval-2010-dv-wc-wordsi-25-stkm-test.key.avg.baseline' using 1:2 title 'Baseline (avg)' lt 2 lc 2 with linespoints, \ + 'semEval-2010-dv-wc-wordsi-25-stkm-test.key.max.actual' using 1:2 title 'Actual (max)' lt 1 lc 3 with linespoints , \ + 'semEval-2010-dv-wc-wordsi-25-stkm-test.key.max.baseline' using 1:2 title 'Baseline (max)' with linespoints + +# +# +# CBC +# +# + +set term postscript eps enhanced color lw 3 "Helvetica" 28 +set output 'semEval-2010-dv-wc-wordsi-25-cbc-test.key.eps' +#set terminal png transparent nocrop enhanced font arial 8 size 500,350 +#set output 'semEval-2010-dv-wc-wordsi-25-cbc-test.key.png' + +#set style histogram #clustered gap 1 +#set style fill solid border 0 + +#binwidth=1 +#set boxwidth binwidth + +set xrange [0.01 : .32] + +set ylabel "Frequency of Sense Confusion" +set xlabel "Ontonote Sense Similarity" + +plot 'semEval-2010-dv-wc-wordsi-25-cbc-test.key.avg.actual' using 1:2 title 'Actual (avg)' with linespoints , \ + 'semEval-2010-dv-wc-wordsi-25-cbc-test.key.avg.baseline' using 1:2 title 'Baseline (avg)' lt 2 lc 2 with linespoints, \ + 'semEval-2010-dv-wc-wordsi-25-cbc-test.key.max.actual' using 1:2 title 'Actual (max)' lt 1 lc 3 with linespoints , \ + 'semEval-2010-dv-wc-wordsi-25-cbc-test.key.max.baseline' using 1:2 title 'Baseline (max)' with linespoints + +# +# +# sc06 +# +# + +set term postscript eps enhanced color lw 3 "Helvetica" 28 +set output 'semEval-2010-dv-wc-wordsi-25-sc06-test.key.eps' +#set terminal png transparent nocrop enhanced font arial 8 size 500,350 +#set output 'semEval-2010-dv-wc-wordsi-25-sc06-test.key.png' + +#set style histogram #clustered gap 1 +#set style fill solid border 0 + +#binwidth=1 +#set boxwidth binwidth + +set xrange [0.01 : .32] + +set ylabel "Frequency of Sense Confusion" +set xlabel "Ontonote Sense Similarity" + +plot 'semEval-2010-dv-wc-wordsi-25-sc06-test.key.avg.actual' using 1:2 title 'Actual (avg)' with linespoints , \ + 'semEval-2010-dv-wc-wordsi-25-sc06-test.key.avg.baseline' using 1:2 title 'Baseline (avg)' lt 2 lc 2 with linespoints, \ + 'semEval-2010-dv-wc-wordsi-25-sc06-test.key.max.actual' using 1:2 title 'Actual (max)' lt 1 lc 3 with linespoints , \ + 'semEval-2010-dv-wc-wordsi-25-sc06-test.key.max.baseline' using 1:2 title 'Baseline (max)' with linespoints + + +# +# +# gs-kmeans +# +# + +set term postscript eps enhanced color lw 3 "Helvetica" 28 +set output 'semEval-2010-dv-wc-wordsi-25-gs-kmeans-test.key.eps' +#set terminal png transparent nocrop enhanced font arial 8 size 500,350 +#set output 'semEval-2010-dv-wc-wordsi-25-gs-kmeans-test.key.png' + +#set style histogram #clustered gap 1 +#set style fill solid border 0 + +#binwidth=1 +#set boxwidth binwidth + +set xrange [0.01 : .32] + +set ylabel "Frequency of Sense Confusion" +set xlabel "Ontonote Sense Similarity" + +plot 'semEval-2010-dv-wc-wordsi-25-gs-kmeans-test.key.avg.actual' using 1:2 title 'Actual (avg)' with linespoints , \ + 'semEval-2010-dv-wc-wordsi-25-gs-kmeans-test.key.avg.baseline' using 1:2 title 'Baseline (avg)' lt 2 lc 2 with linespoints, \ + 'semEval-2010-dv-wc-wordsi-25-gs-kmeans-test.key.max.actual' using 1:2 title 'Actual (max)' lt 1 lc 3 with linespoints , \ + 'semEval-2010-dv-wc-wordsi-25-gs-kmeans-test.key.max.baseline' using 1:2 title 'Baseline (max)' with linespoints \ No newline at end of file diff --git a/papers/2011_emnlp_unsup_impact/code/plots/co-5-plots.all.p b/papers/2011_emnlp_unsup_impact/code/plots/co-5-plots.all.p new file mode 100644 index 00000000..d4b7368b --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/co-5-plots.all.p @@ -0,0 +1,103 @@ +set term postscript eps enhanced color lw 3 "Helvetica" 28 +set output 'semEval-2010-dv-wc-wordsi-stkm-test.key.eps' +#set terminal png transparent nocrop enhanced font arial 8 size 500,350 +#set output 'semEval-2010-dv-wc-wordsi-stkm-test.key.png' + +#set style histogram #clustered gap 1 +#set style fill solid border 0 +set pointsize 2 + +#binwidth=1 +#set boxwidth binwidth + +set xrange [0.01 : .32] + +set ylabel "Frequency of Sense Confusion" +set xlabel "Ontonote Sense Similarity" + +plot 'semEval-2010-dv-wc-wordsi-stkm-test.key.avg.actual' using 1:2 title 'Actual (avg)' lw 2 with linespoints , \ + 'semEval-2010-dv-wc-wordsi-stkm-test.key.avg.baseline' using 1:2 title 'Baseline (avg)' lt 2 lc 2 lw 2 with linespoints, \ + 'semEval-2010-dv-wc-wordsi-stkm-test.key.max.actual' using 1:2 title 'Actual (max)' lt 1 lc 3 lw 2 with linespoints , \ + 'semEval-2010-dv-wc-wordsi-stkm-test.key.max.baseline' using 1:2 title 'Baseline (max)' lt 2 lw 2 lc 4 with linespoints + +# +# +# CBC +# +# + +set term postscript eps enhanced color lw 3 "Helvetica" 28 +set output 'semEval-2010-dv-wc-wordsi-cbc-test.key.eps' +#set terminal png transparent nocrop enhanced font arial 8 size 500,350 +#set output 'semEval-2010-dv-wc-wordsi-cbc-test.key.png' + +#set style histogram #clustered gap 1 +#set style fill solid border 0 + +#binwidth=1 +#set boxwidth binwidth + +set xrange [0.01 : .32] + +set ylabel "Frequency of Sense Confusion" +set xlabel "Ontonote Sense Similarity" + +plot 'semEval-2010-dv-wc-wordsi-cbc-test.key.avg.actual' using 1:2 title 'Actual (avg)' lw 2 with linespoints , \ + 'semEval-2010-dv-wc-wordsi-cbc-test.key.avg.baseline' using 1:2 title 'Baseline (avg)' lw 2 lt 2 lc 2 with linespoints, \ + 'semEval-2010-dv-wc-wordsi-cbc-test.key.max.actual' using 1:2 title 'Actual (max)' lt 1 lc 3 lw 2 with linespoints , \ + 'semEval-2010-dv-wc-wordsi-cbc-test.key.max.baseline' using 1:2 title 'Baseline (max)' lt 2 lw 2 lc 4 with linespoints + +# +# +# sc06 +# +# + +set term postscript eps enhanced color lw 3 "Helvetica" 28 +set output 'semEval-2010-dv-wc-wordsi-sc06-test.key.eps' +#set terminal png transparent nocrop enhanced font arial 8 size 500,350 +#set output 'semEval-2010-dv-wc-wordsi-sc06-test.key.png' + +#set style histogram #clustered gap 1 +#set style fill solid border 0 + +#binwidth=1 +#set boxwidth binwidth + +set xrange [0.01 : .32] + +set ylabel "Frequency of Sense Confusion" +set xlabel "Ontonote Sense Similarity" + +plot 'semEval-2010-dv-wc-wordsi-sc06-test.key.avg.actual' using 1:2 title 'Actual (avg)' lw 2 with linespoints , \ + 'semEval-2010-dv-wc-wordsi-sc06-test.key.avg.baseline' using 1:2 title 'Baseline (avg)' lt 2 lc 2 lw 2 with linespoints, \ + 'semEval-2010-dv-wc-wordsi-sc06-test.key.max.actual' using 1:2 title 'Actual (max)' lt 1 lc 3 lw 2 with linespoints, \ + 'semEval-2010-dv-wc-wordsi-sc06-test.key.max.baseline' using 1:2 title 'Baseline (max)' lt 2 lw 2 lc 4 with linespoints + + +# +# +# gs-kmeans +# +# + +set term postscript eps enhanced color lw 3 "Helvetica" 28 +set output 'semEval-2010-dv-wc-wordsi-gs-kmeans-test.key.eps' +#set terminal png transparent nocrop enhanced font arial 8 size 500,350 +#set output 'semEval-2010-dv-wc-wordsi-gs-kmeans-test.key.png' + +#set style histogram #clustered gap 1 +#set style fill solid border 0 + +#binwidth=1 +#set boxwidth binwidth + +set xrange [0.01 : .32] + +set ylabel "Frequency of Sense Confusion" +set xlabel "Ontonote Sense Similarity" + +plot 'semEval-2010-dv-wc-wordsi-gs-kmeans-test.key.avg.actual' using 1:2 title 'Actual (avg)' lw 2 with linespoints , \ + 'semEval-2010-dv-wc-wordsi-gs-kmeans-test.key.avg.baseline' using 1:2 title 'Baseline (avg)' lt 2 lc 2 lw 2 with linespoints, \ + 'semEval-2010-dv-wc-wordsi-gs-kmeans-test.key.max.actual' using 1:2 title 'Actual (max)' lt 1 lc 3 lw 2 with linespoints , \ + 'semEval-2010-dv-wc-wordsi-gs-kmeans-test.key.max.baseline' using 1:2 title 'Baseline (max)' lt 2 lw 2 lc 4 with linespoints \ No newline at end of file diff --git a/papers/2011_emnlp_unsup_impact/code/plots/dv-rel-plots.all.p b/papers/2011_emnlp_unsup_impact/code/plots/dv-rel-plots.all.p new file mode 100644 index 00000000..ef81e6c9 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/dv-rel-plots.all.p @@ -0,0 +1,103 @@ +set term postscript eps enhanced color lw 3 "Helvetica" 28 +set output 'semEval-2010-dv-wordsi-rel-stkm-test.key.eps' +#set terminal png transparent nocrop enhanced font arial 8 size 500,350 +#set output 'semEval-2010-dv-wordsi-rel-stkm-test.key.png' + +#set style histogram #clustered gap 1 +#set style fill solid border 0 +set pointsize 2 + +#binwidth=1 +#set boxwidth binwidth + +set xrange [0.01 : .32] + +set ylabel "Frequency of Sense Confusion" +set xlabel "Ontonote Sense Similarity" + +plot 'semEval-2010-dv-wordsi-rel-stkm-test.key.avg.actual' using 1:2 title 'Actual (avg)' with linespoints , \ + 'semEval-2010-dv-wordsi-rel-stkm-test.key.avg.baseline' using 1:2 title 'Baseline (avg)' lt 2 lc 2 with linespoints, \ + 'semEval-2010-dv-wordsi-rel-stkm-test.key.max.actual' using 1:2 title 'Actual (max)' lt 1 lc 3 with linespoints , \ + 'semEval-2010-dv-wordsi-rel-stkm-test.key.max.baseline' using 1:2 title 'Baseline (max)' lt 2 lc 4 with linespoints + +# +# +# CBC +# +# + +set term postscript eps enhanced color lw 3 "Helvetica" 28 +set output 'semEval-2010-dv-wordsi-rel-cbc-test.key.eps' +#set terminal png transparent nocrop enhanced font arial 8 size 500,350 +#set output 'semEval-2010-dv-wordsi-rel-cbc-test.key.png' + +#set style histogram #clustered gap 1 +#set style fill solid border 0 + +#binwidth=1 +#set boxwidth binwidth + +set xrange [0.01 : .32] + +set ylabel "Frequency of Sense Confusion" +set xlabel "Ontonote Sense Similarity" + +plot 'semEval-2010-dv-wordsi-rel-cbc-test.key.avg.actual' using 1:2 title 'Actual (avg)' with linespoints , \ + 'semEval-2010-dv-wordsi-rel-cbc-test.key.avg.baseline' using 1:2 title 'Baseline (avg)' lt 2 lc 2 with linespoints, \ + 'semEval-2010-dv-wordsi-rel-cbc-test.key.max.actual' using 1:2 title 'Actual (max)' lt 1 lc 3 with linespoints , \ + 'semEval-2010-dv-wordsi-rel-cbc-test.key.max.baseline' using 1:2 title 'Baseline (max)' with linespoints + +# +# +# sc06 +# +# + +set term postscript eps enhanced color lw 3 "Helvetica" 28 +set output 'semEval-2010-dv-wordsi-rel-sc06-test.key.eps' +#set terminal png transparent nocrop enhanced font arial 8 size 500,350 +#set output 'semEval-2010-dv-wordsi-rel-sc06-test.key.png' + +#set style histogram #clustered gap 1 +#set style fill solid border 0 + +#binwidth=1 +#set boxwidth binwidth + +set xrange [0.01 : .32] + +set ylabel "Frequency of Sense Confusion" +set xlabel "Ontonote Sense Similarity" + +plot 'semEval-2010-dv-wordsi-rel-sc06-test.key.avg.actual' using 1:2 title 'Actual (avg)' with linespoints , \ + 'semEval-2010-dv-wordsi-rel-sc06-test.key.avg.baseline' using 1:2 title 'Baseline (avg)' lt 2 lc 2 with linespoints, \ + 'semEval-2010-dv-wordsi-rel-sc06-test.key.max.actual' using 1:2 title 'Actual (max)' lt 1 lc 3 with linespoints , \ + 'semEval-2010-dv-wordsi-rel-sc06-test.key.max.baseline' using 1:2 title 'Baseline (max)' with linespoints + + +# +# +# gs-kmeans +# +# + +set term postscript eps enhanced color lw 3 "Helvetica" 28 +set output 'semEval-2010-dv-wordsi-rel-gs-kmeans-test.key.eps' +#set terminal png transparent nocrop enhanced font arial 8 size 500,350 +#set output 'semEval-2010-dv-wordsi-rel-gs-kmeans-test.key.png' + +#set style histogram #clustered gap 1 +#set style fill solid border 0 + +#binwidth=1 +#set boxwidth binwidth + +set xrange [0.01 : .32] + +set ylabel "Frequency of Sense Confusion" +set xlabel "Ontonote Sense Similarity" + +plot 'semEval-2010-dv-wordsi-rel-gs-kmeans-test.key.avg.actual' using 1:2 title 'Actual (avg)' with linespoints , \ + 'semEval-2010-dv-wordsi-rel-gs-kmeans-test.key.avg.baseline' using 1:2 title 'Baseline (avg)' lt 2 lc 2! with linespoints, \ + 'semEval-2010-dv-wordsi-rel-gs-kmeans-test.key.max.actual' using 1:2 title 'Actual (max)' lt 1 lc 3 with linespoints , \ + 'semEval-2010-dv-wordsi-rel-gs-kmeans-test.key.max.baseline' using 1:2 title 'Baseline (max)' with linespoints \ No newline at end of file diff --git a/papers/2011_emnlp_unsup_impact/code/plots/order-plots.all.p b/papers/2011_emnlp_unsup_impact/code/plots/order-plots.all.p new file mode 100644 index 00000000..a2ea2202 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/order-plots.all.p @@ -0,0 +1,104 @@ +set term postscript eps enhanced color lw 3 "Helvetica" 28 +set output 'semEval-2010-dv-wc-wordsi-order-stkm-test.key.eps' +#set terminal png transparent nocrop enhanced font arial 8 size 500,350 +#set output 'semEval-2010-dv-wc-wordsi-order-stkm-test.key.png' + +set pointsize 2 + +#set style histogram #clustered gap 1 +#set style fill solid border 0 + +#binwidth=1 +#set boxwidth binwidth + +set xrange [0.01 : .32] + +set ylabel "Frequency of Sense Confusion" +set xlabel "Ontonote Sense Similarity" + +plot 'semEval-2010-dv-wc-wordsi-order-stkm-test.key.avg.actual' using 1:2 title 'Actual (avg)' with linespoints , \ + 'semEval-2010-dv-wc-wordsi-order-stkm-test.key.avg.baseline' using 1:2 title 'Baseline (avg)' lt 2 lc 2 with linespoints, \ + 'semEval-2010-dv-wc-wordsi-order-stkm-test.key.max.actual' using 1:2 title 'Actual (max)' lt 1 lc 3 with linespoints , \ + 'semEval-2010-dv-wc-wordsi-order-stkm-test.key.max.baseline' using 1:2 title 'Baseline (max)' with linespoints + +# +# +# CBC +# +# + +set term postscript eps enhanced color lw 3 "Helvetica" 28 +set output 'semEval-2010-dv-wc-wordsi-order-cbc-test.key.eps' +#set terminal png transparent nocrop enhanced font arial 8 size 500,350 +#set output 'semEval-2010-dv-wc-wordsi-order-cbc-test.key.png' + +#set style histogram #clustered gap 1 +#set style fill solid border 0 + +#binwidth=1 +#set boxwidth binwidth + +set xrange [0.01 : .32] + +set ylabel "Frequency of Sense Confusion" +set xlabel "Ontonote Sense Similarity" + +plot 'semEval-2010-dv-wc-wordsi-order-cbc-test.key.avg.actual' using 1:2 title 'Actual (avg)' with linespoints , \ + 'semEval-2010-dv-wc-wordsi-order-cbc-test.key.avg.baseline' using 1:2 title 'Baseline (avg)' lt 2 lc 2 with linespoints, \ + 'semEval-2010-dv-wc-wordsi-order-cbc-test.key.max.actual' using 1:2 title 'Actual (max)' lt 1 lc 3 with linespoints , \ + 'semEval-2010-dv-wc-wordsi-order-cbc-test.key.max.baseline' using 1:2 title 'Baseline (max)' with linespoints + +# +# +# sc06 +# +# + +set term postscript eps enhanced color lw 3 "Helvetica" 28 +set output 'semEval-2010-dv-wc-wordsi-order-sc06-test.key.eps' +#set terminal png transparent nocrop enhanced font arial 8 size 500,350 +#set output 'semEval-2010-dv-wc-wordsi-order-sc06-test.key.png' + +#set style histogram #clustered gap 1 +#set style fill solid border 0 + +#binwidth=1 +#set boxwidth binwidth + +set xrange [0.01 : .32] + +set ylabel "Frequency of Sense Confusion" +set xlabel "Ontonote Sense Similarity" + +plot 'semEval-2010-dv-wc-wordsi-order-sc06-test.key.avg.actual' using 1:2 title 'Actual (avg)' with linespoints , \ + 'semEval-2010-dv-wc-wordsi-order-sc06-test.key.avg.baseline' using 1:2 title 'Baseline (avg)' lt 2 lc 2 with linespoints, \ + 'semEval-2010-dv-wc-wordsi-order-sc06-test.key.max.actual' using 1:2 title 'Actual (max)' lt 1 lc 3 with linespoints , \ + 'semEval-2010-dv-wc-wordsi-order-sc06-test.key.max.baseline' using 1:2 title 'Baseline (max)' with linespoints + + +# +# +# gs-kmeans +# +# + +set term postscript eps enhanced color lw 3 "Helvetica" 28 +set output 'semEval-2010-dv-wc-wordsi-order-gs-kmeans-test.key.eps' +#set terminal png transparent nocrop enhanced font arial 8 size 500,350 +#set output 'semEval-2010-dv-wc-wordsi-order-gs-kmeans-test.key.png' + +#set style histogram #clustered gap 1 +#set style fill solid border 0 + +#binwidth=1 +#set boxwidth binwidth + +set xrange [0.01 : .32] + +set ylabel "Frequency of Sense Confusion" +set xlabel "Ontonote Sense Similarity" + +plot 'semEval-2010-dv-wc-wordsi-order-gs-kmeans-test.key.avg.actual' using 1:2 title 'Actual (avg)' with linespoints , \ + 'semEval-2010-dv-wc-wordsi-order-gs-kmeans-test.key.avg.baseline' using 1:2 title 'Baseline (avg)' lt 2 lc 2 with linespoints, \ + 'semEval-2010-dv-wc-wordsi-order-gs-kmeans-test.key.max.actual' using 1:2 title 'Actual (max)' lt 1 lc 3 with linespoints , \ + 'semEval-2010-dv-wc-wordsi-order-gs-kmeans-test.key.max.baseline' using 1:2 title 'Baseline (max)' with linespoints \ No newline at end of file diff --git a/papers/2011_emnlp_unsup_impact/code/plots/pos-plots.all.p b/papers/2011_emnlp_unsup_impact/code/plots/pos-plots.all.p new file mode 100644 index 00000000..d85a4bcf --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/pos-plots.all.p @@ -0,0 +1,103 @@ +set term postscript eps enhanced color lw 3 "Helvetica" 28 +set output 'semEval-2010-dv-wc-wordsi-pos-stkm-test.key.eps' +#set terminal png transparent nocrop enhanced font arial 8 size 500,350 +#set output 'semEval-2010-dv-wc-wordsi-pos-stkm-test.key.png' + +#set style histogram #clustered gap 1 +#set style fill solid border 0 +set pointsize 2 + +#binwidth=1 +#set boxwidth binwidth + +set xrange [0.01 : .32] + +set ylabel "Frequency of Sense Confusion" +set xlabel "Ontonote Sense Similarity" + +plot 'semEval-2010-dv-wc-wordsi-pos-stkm-test.key.avg.actual' using 1:2 title 'Actual (avg)' with linespoints , \ + 'semEval-2010-dv-wc-wordsi-pos-stkm-test.key.avg.baseline' using 1:2 title 'Baseline (avg)' lt 2 lc 2 with linespoints, \ + 'semEval-2010-dv-wc-wordsi-pos-stkm-test.key.max.actual' using 1:2 title 'Actual (max)' lt 1 lc 3 with linespoints , \ + 'semEval-2010-dv-wc-wordsi-pos-stkm-test.key.max.baseline' using 1:2 title 'Baseline (max)' with linespoints + +# +# +# CBC +# +# + +set term postscript eps enhanced color lw 3 "Helvetica" 28 +set output 'semEval-2010-dv-wc-wordsi-pos-cbc-test.key.eps' +#set terminal png transparent nocrop enhanced font arial 8 size 500,350 +#set output 'semEval-2010-dv-wc-wordsi-pos-cbc-test.key.png' + +#set style histogram #clustered gap 1 +#set style fill solid border 0 + +#binwidth=1 +#set boxwidth binwidth + +set xrange [0.01 : .32] + +set ylabel "Frequency of Sense Confusion" +set xlabel "Ontonote Sense Similarity" + +plot 'semEval-2010-dv-wc-wordsi-pos-cbc-test.key.avg.actual' using 1:2 title 'Actual (avg)' with linespoints , \ + 'semEval-2010-dv-wc-wordsi-pos-cbc-test.key.avg.baseline' using 1:2 title 'Baseline (avg)' lt 2 lc 2 with linespoints, \ + 'semEval-2010-dv-wc-wordsi-pos-cbc-test.key.max.actual' using 1:2 title 'Actual (max)' lt 1 lc 3 with linespoints , \ + 'semEval-2010-dv-wc-wordsi-pos-cbc-test.key.max.baseline' using 1:2 title 'Baseline (max)' with linespoints + +# +# +# sc06 +# +# + +set term postscript eps enhanced color lw 3 "Helvetica" 28 +set output 'semEval-2010-dv-wc-wordsi-pos-sc06-test.key.eps' +#set terminal png transparent nocrop enhanced font arial 8 size 500,350 +#set output 'semEval-2010-dv-wc-wordsi-pos-sc06-test.key.png' + +#set style histogram #clustered gap 1 +#set style fill solid border 0 + +#binwidth=1 +#set boxwidth binwidth + +set xrange [0.01 : .32] + +set ylabel "Frequency of Sense Confusion" +set xlabel "Ontonote Sense Similarity" + +plot 'semEval-2010-dv-wc-wordsi-pos-sc06-test.key.avg.actual' using 1:2 title 'Actual (avg)' with linespoints , \ + 'semEval-2010-dv-wc-wordsi-pos-sc06-test.key.avg.baseline' using 1:2 title 'Baseline (avg)' lt 2 lc 2 with linespoints, \ + 'semEval-2010-dv-wc-wordsi-pos-sc06-test.key.max.actual' using 1:2 title 'Actual (max)' lt 1 lc 3 with linespoints , \ + 'semEval-2010-dv-wc-wordsi-pos-sc06-test.key.max.baseline' using 1:2 title 'Baseline (max)' with linespoints + + +# +# +# gs-kmeans +# +# + +set term postscript eps enhanced color lw 3 "Helvetica" 28 +set output 'semEval-2010-dv-wc-wordsi-pos-gs-kmeans-test.key.eps' +#set terminal png transparent nocrop enhanced font arial 8 size 500,350 +#set output 'semEval-2010-dv-wc-wordsi-pos-gs-kmeans-test.key.png' + +#set style histogram #clustered gap 1 +#set style fill solid border 0 + +#binwidth=1 +#set boxwidth binwidth + +set xrange [0.01 : .32] + +set ylabel "Frequency of Sense Confusion" +set xlabel "Ontonote Sense Similarity" + +plot 'semEval-2010-dv-wc-wordsi-pos-gs-kmeans-test.key.avg.actual' using 1:2 title 'Actual (avg)' with linespoints , \ + 'semEval-2010-dv-wc-wordsi-pos-gs-kmeans-test.key.avg.baseline' using 1:2 title 'Baseline (avg)' lt 2 lc 2 with linespoints, \ + 'semEval-2010-dv-wc-wordsi-pos-gs-kmeans-test.key.max.actual' using 1:2 title 'Actual (max)' lt 1 lc 3 with linespoints , \ + 'semEval-2010-dv-wc-wordsi-pos-gs-kmeans-test.key.max.baseline' using 1:2 title 'Baseline (max)' with linespoints \ No newline at end of file diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-cbc-test.key.avg.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-cbc-test.key.avg.actual new file mode 100644 index 00000000..cc2cd7e3 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-cbc-test.key.avg.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 76.0 +0.02 38.0 +0.04 157.0 +0.06 110.0 +0.08 71.0 +0.1 44.0 +0.12 20.0 +0.14 15.0 +0.16 2.0 +0.18 24.0 +0.2 11.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-cbc-test.key.avg.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-cbc-test.key.avg.baseline new file mode 100644 index 00000000..12492729 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-cbc-test.key.avg.baseline @@ -0,0 +1,51 @@ +# similarity error_count +0.0 88.11666666666666 +0.02 46.833333333333336 +0.04 179.66666666666666 +0.06 120.9 +0.08 69.61666666666666 +0.1 21.55 +0.12 19.25 +0.14 8.5 +0.16 2.0 +0.18 6.5 +0.2 5.0666666666666655 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-cbc-test.key.eps b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-cbc-test.key.eps new file mode 100644 index 00000000..f5ad8c96 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-cbc-test.key.eps @@ -0,0 +1,819 @@ +%!PS-Adobe-2.0 EPSF-2.0 +%%Title: semEval-2010-dv-wc-wordsi-25-cbc-test.key.eps +%%Creator: gnuplot 4.3 patchlevel 0 +%%CreationDate: Sun May 15 23:41:17 2011 +%%DocumentFonts: (atend) +%%BoundingBox: 50 50 410 302 +%%EndComments +%%BeginProlog +/gnudict 256 dict def +gnudict begin +% +% The following true/false flags may be edited by hand if desired. +% The unit 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/dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-cbc-test.key.max.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 69.0 +0.02 0.0 +0.04 102.0 +0.06 204.0 +0.08 56.0 +0.1 35.0 +0.12 29.0 +0.14 0.0 +0.16 2.0 +0.18 39.0 +0.2 6.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 21.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 5.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-cbc-test.key.max.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-cbc-test.key.max.baseline new file mode 100644 index 00000000..4e496271 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-cbc-test.key.max.baseline @@ -0,0 +1,51 @@ +# similarity error_count +0.0 81.61666666666666 +0.02 0.0 +0.04 158.38333333333333 +0.06 185.13333333333335 +0.08 62.2 +0.1 23.05 +0.12 24.25 +0.14 0.0 +0.16 2.8 +0.18 15.0 +0.2 2.4 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 10.5 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 2.6666666666666665 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-gs-kmeans-test.key.avg.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-gs-kmeans-test.key.avg.actual new file mode 100644 index 00000000..9456cafe --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-gs-kmeans-test.key.avg.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 221.0 +0.02 74.0 +0.04 285.0 +0.06 150.0 +0.08 174.0 +0.1 74.0 +0.12 59.0 +0.14 41.0 +0.16 16.0 +0.18 69.0 +0.2 24.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-gs-kmeans-test.key.avg.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-gs-kmeans-test.key.avg.baseline new file mode 100644 index 00000000..8996b7dc --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-gs-kmeans-test.key.avg.baseline @@ -0,0 +1,51 @@ +# similarity error_count +0.0 208.2333333333346 +0.02 95.91666666666666 +0.04 361.46666666666687 +0.06 266.19999999999993 +0.08 151.96666666666667 +0.1 31.450000000000003 +0.12 14.75 +0.14 20.5 +0.16 12.333333333333332 +0.18 17.25 +0.2 6.933333333333332 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-gs-kmeans-test.key.eps 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{closepath} bind def +/C {setrgbcolor} bind def +/f {rlineto fill} bind def +/Gshow {show} def % May be redefined later in the file to support UTF-8 +/vpt2 vpt 2 mul def +/hpt2 hpt 2 mul def +/Lshow {currentpoint stroke M 0 vshift R + Blacktext {gsave 0 setgray show grestore} {show} ifelse} def +/Rshow {currentpoint stroke M dup stringwidth pop neg vshift R + Blacktext {gsave 0 setgray show grestore} {show} ifelse} def +/Cshow {currentpoint stroke M dup stringwidth pop -2 div vshift R + Blacktext {gsave 0 setgray show grestore} {show} ifelse} def +/UP {dup vpt_ mul /vpt exch def hpt_ mul /hpt exch def + /hpt2 hpt 2 mul def /vpt2 vpt 2 mul def} def +/DL {Color {setrgbcolor Solid {pop []} if 0 setdash} + {pop pop pop 0 setgray Solid {pop []} if 0 setdash} ifelse} def +/BL {stroke userlinewidth 2 mul setlinewidth + Rounded {1 setlinejoin 1 setlinecap} if} def +/AL {stroke userlinewidth 2 div setlinewidth + Rounded {1 setlinejoin 1 setlinecap} if} def +/UL {dup gnulinewidth mul /userlinewidth exch def + dup 1 lt {pop 1} if 10 mul /udl exch def} def +/PL {stroke userlinewidth setlinewidth + Rounded {1 setlinejoin 1 setlinecap} if} def +% Default Line colors +/LCw {1 1 1} def +/LCb {0 0 0} def +/LCa {0 0 0} def +/LC0 {1 0 0} def +/LC1 {0 1 0} def +/LC2 {0 0 1} def +/LC3 {1 0 1} def +/LC4 {0 1 1} def +/LC5 {1 1 0} def +/LC6 {0 0 0} def +/LC7 {1 0.3 0} def +/LC8 {0.5 0.5 0.5} def +% Default Line Types +/LTw {PL [] 1 setgray} def +/LTb {BL [] LCb DL} def +/LTa {AL [1 udl mul 2 udl mul] 0 setdash LCa setrgbcolor} def +/LT0 {PL [] LC0 DL} def +/LT1 {PL [4 dl1 2 dl2] LC1 DL} def +/LT2 {PL [2 dl1 3 dl2] LC2 DL} def +/LT3 {PL [1 dl1 1.5 dl2] LC3 DL} def +/LT4 {PL [6 dl1 2 dl2 1 dl1 2 dl2] LC4 DL} def +/LT5 {PL [3 dl1 3 dl2 1 dl1 3 dl2] LC5 DL} def +/LT6 {PL [2 dl1 2 dl2 2 dl1 6 dl2] LC6 DL} def +/LT7 {PL [1 dl1 2 dl2 6 dl1 2 dl2 1 dl1 2 dl2] LC7 DL} def +/LT8 {PL [2 dl1 2 dl2 2 dl1 2 dl2 2 dl1 2 dl2 2 dl1 4 dl2] LC8 DL} def +/Pnt {stroke [] 0 setdash gsave 1 setlinecap M 0 0 V stroke grestore} def +/Dia {stroke [] 0 setdash 2 copy vpt add M + hpt neg vpt neg V hpt vpt neg V + hpt vpt V hpt neg vpt V closepath stroke + Pnt} def +/Pls {stroke [] 0 setdash vpt sub M 0 vpt2 V + currentpoint stroke M + hpt neg vpt neg R hpt2 0 V stroke + } def +/Box {stroke [] 0 setdash 2 copy exch hpt sub exch vpt add M + 0 vpt2 neg V hpt2 0 V 0 vpt2 V + hpt2 neg 0 V closepath stroke + Pnt} def +/Crs {stroke [] 0 setdash exch hpt sub exch vpt add M + hpt2 vpt2 neg V currentpoint stroke M + hpt2 neg 0 R hpt2 vpt2 V stroke} def +/TriU {stroke [] 0 setdash 2 copy vpt 1.12 mul add M + hpt neg vpt -1.62 mul V + hpt 2 mul 0 V + hpt neg vpt 1.62 mul V closepath stroke + Pnt} def +/Star {2 copy Pls Crs} def +/BoxF {stroke [] 0 setdash exch hpt sub exch vpt add M + 0 vpt2 neg V hpt2 0 V 0 vpt2 V + hpt2 neg 0 V closepath fill} def +/TriUF {stroke [] 0 setdash vpt 1.12 mul add M + hpt neg vpt -1.62 mul V + hpt 2 mul 0 V + hpt neg vpt 1.62 mul V closepath fill} def +/TriD {stroke [] 0 setdash 2 copy vpt 1.12 mul sub M + hpt neg vpt 1.62 mul V + hpt 2 mul 0 V + hpt neg vpt -1.62 mul V closepath stroke + Pnt} def +/TriDF {stroke [] 0 setdash vpt 1.12 mul sub M + hpt neg vpt 1.62 mul V + hpt 2 mul 0 V + hpt neg vpt -1.62 mul V closepath fill} def +/DiaF {stroke [] 0 setdash vpt add M + hpt neg vpt neg V hpt vpt neg V + hpt vpt V hpt neg vpt V closepath fill} def +/Pent {stroke [] 0 setdash 2 copy gsave + translate 0 hpt M 4 {72 rotate 0 hpt L} repeat + closepath stroke grestore Pnt} def +/PentF {stroke [] 0 setdash gsave + translate 0 hpt M 4 {72 rotate 0 hpt L} repeat + closepath fill grestore} def +/Circle {stroke [] 0 setdash 2 copy + hpt 0 360 arc stroke Pnt} def +/CircleF {stroke [] 0 setdash hpt 0 360 arc fill} def +/C0 {BL [] 0 setdash 2 copy moveto vpt 90 450 arc} bind def +/C1 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 0 90 arc closepath fill + vpt 0 360 arc closepath} bind def +/C2 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 90 180 arc closepath fill + vpt 0 360 arc closepath} bind def +/C3 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 0 180 arc closepath fill + vpt 0 360 arc closepath} bind def +/C4 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 180 270 arc closepath fill + vpt 0 360 arc closepath} bind def +/C5 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 0 90 arc + 2 copy moveto + 2 copy vpt 180 270 arc closepath fill + vpt 0 360 arc} bind def +/C6 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 90 270 arc closepath fill + vpt 0 360 arc closepath} bind def +/C7 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 0 270 arc closepath fill + vpt 0 360 arc closepath} bind def +/C8 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 270 360 arc closepath fill + vpt 0 360 arc closepath} bind def +/C9 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 270 450 arc closepath fill + vpt 0 360 arc closepath} bind def +/C10 {BL [] 0 setdash 2 copy 2 copy moveto vpt 270 360 arc closepath fill + 2 copy moveto + 2 copy vpt 90 180 arc closepath fill + vpt 0 360 arc closepath} bind def +/C11 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 0 180 arc closepath fill + 2 copy moveto + 2 copy vpt 270 360 arc closepath fill + vpt 0 360 arc closepath} bind def +/C12 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 180 360 arc closepath fill + vpt 0 360 arc closepath} bind def +/C13 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 0 90 arc closepath fill + 2 copy moveto + 2 copy vpt 180 360 arc closepath fill + vpt 0 360 arc closepath} bind def +/C14 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 90 360 arc closepath fill + vpt 0 360 arc} bind def +/C15 {BL [] 0 setdash 2 copy vpt 0 360 arc closepath fill + vpt 0 360 arc closepath} bind def +/Rec {newpath 4 2 roll moveto 1 index 0 rlineto 0 exch rlineto + neg 0 rlineto closepath} bind def +/Square {dup Rec} bind def +/Bsquare {vpt sub exch vpt sub exch vpt2 Square} bind def +/S0 {BL [] 0 setdash 2 copy moveto 0 vpt rlineto BL Bsquare} bind def +/S1 {BL [] 0 setdash 2 copy vpt Square fill Bsquare} bind def +/S2 {BL [] 0 setdash 2 copy exch vpt sub exch vpt Square fill Bsquare} bind def +/S3 {BL [] 0 setdash 2 copy exch vpt sub exch vpt2 vpt Rec fill Bsquare} bind def +/S4 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt Square fill Bsquare} bind def +/S5 {BL [] 0 setdash 2 copy 2 copy vpt Square fill + exch vpt sub exch vpt sub vpt Square fill Bsquare} bind def +/S6 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt vpt2 Rec fill Bsquare} bind def +/S7 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt vpt2 Rec fill + 2 copy vpt Square fill Bsquare} bind def +/S8 {BL [] 0 setdash 2 copy vpt sub vpt Square fill Bsquare} bind def +/S9 {BL [] 0 setdash 2 copy vpt sub vpt vpt2 Rec fill Bsquare} bind def +/S10 {BL [] 0 setdash 2 copy vpt sub vpt Square fill 2 copy exch vpt sub exch vpt Square fill + Bsquare} bind def +/S11 {BL [] 0 setdash 2 copy vpt sub vpt Square fill 2 copy exch vpt sub exch vpt2 vpt Rec fill + Bsquare} bind def +/S12 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt2 vpt Rec fill Bsquare} bind def +/S13 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt2 vpt Rec fill + 2 copy vpt Square fill Bsquare} bind def +/S14 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt2 vpt Rec fill + 2 copy exch vpt sub exch vpt Square fill Bsquare} bind def +/S15 {BL [] 0 setdash 2 copy Bsquare fill Bsquare} bind def +/D0 {gsave translate 45 rotate 0 0 S0 stroke grestore} bind def +/D1 {gsave translate 45 rotate 0 0 S1 stroke grestore} bind def +/D2 {gsave translate 45 rotate 0 0 S2 stroke grestore} bind def +/D3 {gsave translate 45 rotate 0 0 S3 stroke grestore} bind def +/D4 {gsave translate 45 rotate 0 0 S4 stroke grestore} bind def +/D5 {gsave translate 45 rotate 0 0 S5 stroke grestore} bind def +/D6 {gsave translate 45 rotate 0 0 S6 stroke grestore} bind def +/D7 {gsave translate 45 rotate 0 0 S7 stroke grestore} bind def +/D8 {gsave translate 45 rotate 0 0 S8 stroke grestore} bind def +/D9 {gsave translate 45 rotate 0 0 S9 stroke grestore} bind def +/D10 {gsave translate 45 rotate 0 0 S10 stroke grestore} bind def +/D11 {gsave translate 45 rotate 0 0 S11 stroke grestore} bind def +/D12 {gsave translate 45 rotate 0 0 S12 stroke grestore} bind def +/D13 {gsave translate 45 rotate 0 0 S13 stroke grestore} bind def +/D14 {gsave translate 45 rotate 0 0 S14 stroke grestore} bind def +/D15 {gsave translate 45 rotate 0 0 S15 stroke grestore} bind def +/DiaE {stroke [] 0 setdash vpt add M + hpt neg vpt neg V hpt vpt neg V + hpt vpt V hpt neg vpt V closepath stroke} def +/BoxE {stroke [] 0 setdash exch hpt sub exch vpt add M + 0 vpt2 neg V hpt2 0 V 0 vpt2 V + hpt2 neg 0 V closepath stroke} def +/TriUE {stroke [] 0 setdash vpt 1.12 mul add M + hpt neg vpt -1.62 mul V + hpt 2 mul 0 V + hpt neg vpt 1.62 mul V closepath stroke} def +/TriDE {stroke [] 0 setdash vpt 1.12 mul sub M + hpt neg vpt 1.62 mul V + hpt 2 mul 0 V + hpt neg vpt -1.62 mul V closepath stroke} def +/PentE {stroke [] 0 setdash gsave + translate 0 hpt M 4 {72 rotate 0 hpt L} repeat + closepath stroke grestore} def +/CircE {stroke [] 0 setdash + hpt 0 360 arc stroke} def +/Opaque {gsave closepath 1 setgray fill grestore 0 setgray closepath} def +/DiaW {stroke [] 0 setdash vpt add M + hpt neg vpt neg V hpt vpt neg V + hpt vpt V hpt neg vpt V Opaque stroke} def +/BoxW {stroke [] 0 setdash exch hpt sub exch vpt add M + 0 vpt2 neg V hpt2 0 V 0 vpt2 V + hpt2 neg 0 V Opaque stroke} def +/TriUW {stroke [] 0 setdash vpt 1.12 mul add M + hpt neg vpt -1.62 mul V + hpt 2 mul 0 V + hpt neg vpt 1.62 mul V Opaque stroke} def +/TriDW {stroke [] 0 setdash vpt 1.12 mul sub M + hpt neg vpt 1.62 mul V + hpt 2 mul 0 V + hpt neg vpt -1.62 mul V Opaque stroke} def +/PentW {stroke [] 0 setdash gsave + translate 0 hpt M 4 {72 rotate 0 hpt L} repeat + Opaque stroke grestore} def +/CircW {stroke [] 0 setdash + hpt 0 360 arc Opaque stroke} def +/BoxFill {gsave Rec 1 setgray fill grestore} def +/Density { + /Fillden exch def + currentrgbcolor + /ColB exch def /ColG exch def /ColR exch def + /ColR ColR Fillden mul Fillden sub 1 add def + /ColG ColG Fillden mul Fillden sub 1 add def + /ColB ColB Fillden mul Fillden sub 1 add def + ColR ColG ColB setrgbcolor} def +/BoxColFill {gsave Rec PolyFill} def +/PolyFill {gsave Density fill grestore grestore} def +/h {rlineto rlineto rlineto gsave closepath fill grestore} bind def +% +% PostScript Level 1 Pattern Fill routine for rectangles +% Usage: x y w h s a XX PatternFill +% x,y = lower left corner of box to be filled +% w,h = width and height of box +% a = angle in degrees between lines and x-axis +% XX = 0/1 for no/yes cross-hatch +% +/PatternFill {gsave /PFa [ 9 2 roll ] def + PFa 0 get PFa 2 get 2 div add PFa 1 get PFa 3 get 2 div add translate + PFa 2 get -2 div PFa 3 get -2 div PFa 2 get PFa 3 get Rec + gsave 1 setgray fill grestore clip + currentlinewidth 0.5 mul setlinewidth + /PFs PFa 2 get dup mul PFa 3 get dup mul add sqrt def + 0 0 M PFa 5 get rotate PFs -2 div dup translate + 0 1 PFs PFa 4 get div 1 add floor cvi + {PFa 4 get mul 0 M 0 PFs V} for + 0 PFa 6 get ne { + 0 1 PFs PFa 4 get div 1 add floor cvi + {PFa 4 get mul 0 2 1 roll M PFs 0 V} for + } if + stroke grestore} def +% +/languagelevel where + {pop languagelevel} {1} ifelse + 2 lt + {/InterpretLevel1 true def} + {/InterpretLevel1 Level1 def} + ifelse +% +% PostScript level 2 pattern fill definitions +% +/Level2PatternFill { +/Tile8x8 {/PaintType 2 /PatternType 1 /TilingType 1 /BBox [0 0 8 8] /XStep 8 /YStep 8} + bind def +/KeepColor {currentrgbcolor [/Pattern /DeviceRGB] setcolorspace} bind def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 0 M 8 8 L 0 8 M 8 0 L stroke} +>> matrix makepattern +/Pat1 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 0 M 8 8 L 0 8 M 8 0 L stroke + 0 4 M 4 8 L 8 4 L 4 0 L 0 4 L stroke} +>> matrix makepattern +/Pat2 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 0 M 0 8 L + 8 8 L 8 0 L 0 0 L fill} +>> matrix makepattern +/Pat3 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -4 8 M 8 -4 L + 0 12 M 12 0 L stroke} +>> matrix makepattern +/Pat4 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -4 0 M 8 12 L + 0 -4 M 12 8 L stroke} +>> matrix makepattern +/Pat5 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -2 8 M 4 -4 L + 0 12 M 8 -4 L 4 12 M 10 0 L stroke} +>> matrix makepattern +/Pat6 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -2 0 M 4 12 L + 0 -4 M 8 12 L 4 -4 M 10 8 L stroke} +>> matrix makepattern +/Pat7 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 8 -2 M -4 4 L + 12 0 M -4 8 L 12 4 M 0 10 L stroke} +>> matrix makepattern +/Pat8 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 -2 M 12 4 L + -4 0 M 12 8 L -4 4 M 8 10 L stroke} +>> matrix makepattern +/Pat9 exch def +/Pattern1 {PatternBgnd KeepColor Pat1 setpattern} bind def +/Pattern2 {PatternBgnd KeepColor Pat2 setpattern} bind def +/Pattern3 {PatternBgnd KeepColor Pat3 setpattern} bind def +/Pattern4 {PatternBgnd KeepColor Landscape {Pat5} {Pat4} ifelse setpattern} bind def +/Pattern5 {PatternBgnd KeepColor Landscape {Pat4} {Pat5} ifelse setpattern} bind def +/Pattern6 {PatternBgnd KeepColor Landscape {Pat9} {Pat6} ifelse setpattern} bind def +/Pattern7 {PatternBgnd KeepColor Landscape {Pat8} {Pat7} ifelse setpattern} bind def +} def +% +% +%End of PostScript Level 2 code +% +/PatternBgnd { + TransparentPatterns {} {gsave 1 setgray fill grestore} ifelse +} def +% +% Substitute for Level 2 pattern fill codes with +% grayscale if Level 2 support is not selected. +% +/Level1PatternFill { +/Pattern1 {0.250 Density} bind def +/Pattern2 {0.500 Density} bind def +/Pattern3 {0.750 Density} bind def +/Pattern4 {0.125 Density} bind def +/Pattern5 {0.375 Density} bind def +/Pattern6 {0.625 Density} bind def +/Pattern7 {0.875 Density} bind def +} def +% +% Now test for support of Level 2 code +% +Level1 {Level1PatternFill} {Level2PatternFill} ifelse +% +/Symbol-Oblique /Symbol findfont [1 0 .167 1 0 0] makefont +dup length dict begin {1 index /FID eq {pop pop} {def} ifelse} forall +currentdict end definefont pop +/MFshow { + { dup 5 get 3 ge + { 5 get 3 eq {gsave} {grestore} ifelse } + {dup dup 0 get findfont exch 1 get scalefont setfont + [ currentpoint ] exch dup 2 get 0 exch R dup 5 get 2 ne {dup dup 6 + get exch 4 get {Gshow} {stringwidth pop 0 R} ifelse }if dup 5 get 0 eq + {dup 3 get {2 get neg 0 exch R pop} {pop aload pop M} ifelse} {dup 5 + get 1 eq {dup 2 get exch dup 3 get exch 6 get stringwidth pop -2 div + dup 0 R} {dup 6 get stringwidth pop -2 div 0 R 6 get + show 2 index {aload pop M neg 3 -1 roll neg R pop pop} {pop pop pop + pop aload pop M} ifelse }ifelse }ifelse } + ifelse } + forall} def +/Gswidth {dup type /stringtype eq {stringwidth} {pop (n) stringwidth} ifelse} def +/MFwidth {0 exch { dup 5 get 3 ge { 5 get 3 eq { 0 } { pop } ifelse } + {dup 3 get{dup dup 0 get findfont exch 1 get scalefont setfont + 6 get Gswidth pop add} {pop} ifelse} ifelse} forall} def +/MLshow { currentpoint stroke M + 0 exch R + Blacktext {gsave 0 setgray MFshow grestore} {MFshow} ifelse } bind def +/MRshow { currentpoint stroke M + exch dup MFwidth neg 3 -1 roll R + Blacktext {gsave 0 setgray MFshow grestore} {MFshow} ifelse } bind def +/MCshow { currentpoint stroke M + exch dup MFwidth -2 div 3 -1 roll R + Blacktext {gsave 0 setgray MFshow grestore} {MFshow} ifelse } bind def +/XYsave { [( ) 1 2 true false 3 ()] } bind def +/XYrestore { [( ) 1 2 true false 4 ()] } bind def +end +%%EndProlog +gnudict begin +gsave +doclip +50 50 translate +0.050 0.050 scale +0 setgray +newpath +(Helvetica) findfont 280 scalefont setfont +1.000 UL +LTb +1540 896 M +63 0 V +5176 0 R +-63 0 V +stroke +1372 896 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 0)] +] -93.3 MRshow +1.000 UL +LTb +1540 1372 M +63 0 V +5176 0 R +-63 0 V +stroke +1372 1372 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 50)] +] -93.3 MRshow +1.000 UL +LTb +1540 1848 M +63 0 V +5176 0 R +-63 0 V +stroke +1372 1848 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 100)] +] 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true 0 (Ontonote Sense Similarity)] +] -93.3 MCshow +LTb +2.000 UP +1.000 UL +LTb +% Begin plot #1 +2.000 UP +1.000 UL +LT0 +LCb setrgbcolor +5477 4500 M +[ [(Helvetica) 280.0 0.0 true true 0 (Actual \(avg\))] +] -93.3 MRshow +LT0 +5645 4500 M +798 0 V +1540 2300 M +169 -700 V +338 2008 V +2385 2324 L +338 228 V +338 -952 V +338 -142 V +338 -172 V +338 -238 V +338 505 V +338 -429 V +5089 896 L +338 0 V +338 0 V +338 0 V +338 0 V +338 0 V +1709 1600 Pls +2047 3608 Pls +2385 2324 Pls +2723 2552 Pls +3061 1600 Pls +3399 1458 Pls +3737 1286 Pls +4075 1048 Pls +4413 1553 Pls +4751 1124 Pls +5089 896 Pls +5427 896 Pls +5765 896 Pls +6103 896 Pls +6441 896 Pls +6779 896 Pls +6044 4500 Pls +% End plot #1 +% Begin plot #2 +2.000 UP +1.000 UL +LT1 +LC1 setrgbcolor +LCb setrgbcolor +5477 4220 M +[ [(Helvetica) 280.0 0.0 true true 0 (Baseline \(avg\))] +] -93.3 MRshow +LT1 +LC1 setrgbcolor +5645 4220 M +798 0 V +1540 2343 M +169 -534 V +338 2527 V +338 -906 V +2723 2342 L +3061 1195 L +338 -159 V 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Star +6044 3940 Star +% End plot #3 +% Begin plot #4 +2.000 UP +1.000 UL +LT3 +LCb setrgbcolor +5477 3660 M +[ [(Helvetica) 280.0 0.0 true true 0 (Baseline \(max\))] +] -93.3 MRshow +LT3 +5645 3660 M +798 0 V +1540 1801 M +1709 896 L +338 3382 V +338 22 V +2723 2073 L +338 -553 V +338 -430 V +3737 896 L +338 144 V +338 215 V +4751 911 L +338 -7 V +338 -8 V +338 0 V +338 0 V +338 128 V +6779 896 L +1709 896 Box +2047 4278 Box +2385 4300 Box +2723 2073 Box +3061 1520 Box +3399 1090 Box +3737 896 Box +4075 1040 Box +4413 1255 Box +4751 911 Box +5089 904 Box +5427 896 Box +5765 896 Box +6103 896 Box +6441 1024 Box +6779 896 Box +6044 3660 Box +% End plot #4 +1.000 UL +LTb +1540 4703 N +0 -3807 V +5239 0 V +0 3807 V +-5239 0 V +Z stroke +2.000 UP +1.000 UL +LTb +stroke +grestore +end +showpage +%%Trailer +%%DocumentFonts: Helvetica diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-gs-kmeans-test.key.max.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-gs-kmeans-test.key.max.actual new file mode 100644 index 00000000..614c4b43 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-gs-kmeans-test.key.max.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 206.0 +0.02 0.0 +0.04 213.0 +0.06 300.0 +0.08 140.0 +0.1 75.0 +0.12 76.0 +0.14 0.0 +0.16 16.0 +0.18 110.0 +0.2 8.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 27.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 16.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-gs-kmeans-test.key.max.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-gs-kmeans-test.key.max.baseline new file mode 100644 index 00000000..34cea07e --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-gs-kmeans-test.key.max.baseline @@ -0,0 +1,51 @@ +# similarity error_count +0.0 190.2333333333346 +0.02 0.0 +0.04 355.3333333333334 +0.06 357.65000000000003 +0.08 123.70000000000002 +0.1 65.55000000000001 +0.12 20.416666666666664 +0.14 0.0 +0.16 15.133333333333331 +0.18 37.75 +0.2 1.5999999999999999 +0.22 0.8 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 13.5 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 5.333333333333332 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-sc06-test.key.avg.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-sc06-test.key.avg.actual new file mode 100644 index 00000000..e1848bf9 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-sc06-test.key.avg.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 219.0 +0.02 70.0 +0.04 272.0 +0.06 155.0 +0.08 181.0 +0.1 74.0 +0.12 59.0 +0.14 23.0 +0.16 16.0 +0.18 56.0 +0.2 24.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-sc06-test.key.avg.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-sc06-test.key.avg.baseline new file mode 100644 index 00000000..069087e2 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-sc06-test.key.avg.baseline @@ -0,0 +1,51 @@ +# similarity error_count +0.0 200.33333333333445 +0.02 92.08333333333333 +0.04 363.78333333333353 +0.06 251.06666666666663 +0.08 132.26666666666668 +0.1 31.450000000000003 +0.12 14.75 +0.14 30.0 +0.16 12.333333333333332 +0.18 14.0 +0.2 6.933333333333332 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 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a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-sc06-test.key.max.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-sc06-test.key.max.actual new file mode 100644 index 00000000..3f0446b2 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-sc06-test.key.max.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 204.0 +0.02 0.0 +0.04 201.0 +0.06 298.0 +0.08 133.0 +0.1 91.0 +0.12 76.0 +0.14 0.0 +0.16 16.0 +0.18 79.0 +0.2 8.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 27.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 16.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-sc06-test.key.max.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-sc06-test.key.max.baseline new file mode 100644 index 00000000..64e61577 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-sc06-test.key.max.baseline @@ -0,0 +1,51 @@ +# similarity error_count +0.0 182.33333333333445 +0.02 0.0 +0.04 359.5666666666668 +0.06 338.66666666666674 +0.08 116.9 +0.1 50.75 +0.12 20.416666666666664 +0.14 0.0 +0.16 15.133333333333331 +0.18 44.0 +0.2 1.5999999999999999 +0.22 0.8 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 13.5 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 5.333333333333332 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-stkm-test.key.avg.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-stkm-test.key.avg.actual new file mode 100644 index 00000000..9456cafe --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-stkm-test.key.avg.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 221.0 +0.02 74.0 +0.04 285.0 +0.06 150.0 +0.08 174.0 +0.1 74.0 +0.12 59.0 +0.14 41.0 +0.16 16.0 +0.18 69.0 +0.2 24.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-stkm-test.key.avg.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-stkm-test.key.avg.baseline new file mode 100644 index 00000000..8996b7dc --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-stkm-test.key.avg.baseline @@ -0,0 +1,51 @@ +# similarity error_count +0.0 208.2333333333346 +0.02 95.91666666666666 +0.04 361.46666666666687 +0.06 266.19999999999993 +0.08 151.96666666666667 +0.1 31.450000000000003 +0.12 14.75 +0.14 20.5 +0.16 12.333333333333332 +0.18 17.25 +0.2 6.933333333333332 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-stkm-test.key.eps b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-stkm-test.key.eps new file mode 100644 index 00000000..e804bbc9 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-stkm-test.key.eps @@ -0,0 +1,849 @@ +%!PS-Adobe-2.0 EPSF-2.0 +%%Title: semEval-2010-dv-wc-wordsi-25-stkm-test.key.eps +%%Creator: gnuplot 4.3 patchlevel 0 +%%CreationDate: Sun May 15 23:41:17 2011 +%%DocumentFonts: (atend) +%%BoundingBox: 50 50 410 302 +%%EndComments +%%BeginProlog +/gnudict 256 dict def +gnudict begin +% +% The following true/false flags may be edited by hand if desired. +% The unit line width and grayscale image gamma correction may also be changed. +% +/Color true def +/Blacktext false def +/Solid false def +/Dashlength 1 def +/Landscape false def +/Level1 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Prolog Version 4.2 (November 2007) +% +/M {moveto} bind def +/L {lineto} bind def +/R {rmoveto} bind def +/V {rlineto} bind def +/N {newpath moveto} bind def +/Z {closepath} bind def +/C {setrgbcolor} bind def +/f {rlineto fill} bind def +/Gshow {show} def % May be redefined later in the file to support UTF-8 +/vpt2 vpt 2 mul def +/hpt2 hpt 2 mul def +/Lshow {currentpoint stroke M 0 vshift R + Blacktext {gsave 0 setgray show grestore} {show} ifelse} def +/Rshow {currentpoint stroke M dup stringwidth pop neg vshift R + Blacktext {gsave 0 setgray show grestore} {show} ifelse} def +/Cshow {currentpoint stroke M dup stringwidth pop -2 div vshift R + Blacktext {gsave 0 setgray show grestore} {show} ifelse} def +/UP {dup vpt_ mul /vpt exch def hpt_ mul /hpt exch def + /hpt2 hpt 2 mul def /vpt2 vpt 2 mul def} def +/DL {Color {setrgbcolor Solid {pop []} if 0 setdash} + {pop pop pop 0 setgray Solid {pop []} if 0 setdash} ifelse} def +/BL {stroke userlinewidth 2 mul setlinewidth + Rounded {1 setlinejoin 1 setlinecap} if} def +/AL {stroke userlinewidth 2 div setlinewidth + Rounded {1 setlinejoin 1 setlinecap} if} def +/UL {dup gnulinewidth mul /userlinewidth exch def + dup 1 lt {pop 1} if 10 mul /udl exch def} def +/PL {stroke userlinewidth setlinewidth + Rounded {1 setlinejoin 1 setlinecap} if} def +% Default Line colors +/LCw {1 1 1} def +/LCb {0 0 0} def +/LCa {0 0 0} def +/LC0 {1 0 0} def +/LC1 {0 1 0} def +/LC2 {0 0 1} def +/LC3 {1 0 1} def +/LC4 {0 1 1} def +/LC5 {1 1 0} def +/LC6 {0 0 0} def +/LC7 {1 0.3 0} def +/LC8 {0.5 0.5 0.5} def +% Default Line Types +/LTw {PL [] 1 setgray} def +/LTb {BL [] LCb DL} def +/LTa {AL [1 udl mul 2 udl mul] 0 setdash LCa setrgbcolor} def +/LT0 {PL [] LC0 DL} def +/LT1 {PL [4 dl1 2 dl2] LC1 DL} def +/LT2 {PL [2 dl1 3 dl2] LC2 DL} def +/LT3 {PL [1 dl1 1.5 dl2] LC3 DL} def +/LT4 {PL [6 dl1 2 dl2 1 dl1 2 dl2] LC4 DL} def +/LT5 {PL [3 dl1 3 dl2 1 dl1 3 dl2] LC5 DL} def +/LT6 {PL [2 dl1 2 dl2 2 dl1 6 dl2] LC6 DL} def +/LT7 {PL [1 dl1 2 dl2 6 dl1 2 dl2 1 dl1 2 dl2] LC7 DL} def +/LT8 {PL [2 dl1 2 dl2 2 dl1 2 dl2 2 dl1 2 dl2 2 dl1 4 dl2] LC8 DL} def +/Pnt {stroke [] 0 setdash gsave 1 setlinecap M 0 0 V stroke grestore} def +/Dia {stroke [] 0 setdash 2 copy vpt add M + hpt neg vpt neg V hpt vpt neg V + hpt vpt V hpt neg vpt V closepath stroke + Pnt} def +/Pls {stroke [] 0 setdash vpt sub M 0 vpt2 V + currentpoint stroke M + hpt neg vpt neg R hpt2 0 V stroke + } def +/Box {stroke [] 0 setdash 2 copy exch hpt sub exch vpt add M + 0 vpt2 neg V hpt2 0 V 0 vpt2 V + hpt2 neg 0 V closepath stroke + Pnt} def +/Crs {stroke [] 0 setdash exch hpt sub exch vpt add M + hpt2 vpt2 neg V currentpoint stroke M + hpt2 neg 0 R hpt2 vpt2 V stroke} def +/TriU {stroke [] 0 setdash 2 copy vpt 1.12 mul add M + hpt neg vpt -1.62 mul V + hpt 2 mul 0 V + hpt neg vpt 1.62 mul V closepath stroke + Pnt} def +/Star {2 copy Pls Crs} def +/BoxF {stroke [] 0 setdash exch hpt sub exch vpt add M + 0 vpt2 neg V hpt2 0 V 0 vpt2 V + hpt2 neg 0 V closepath fill} def +/TriUF {stroke [] 0 setdash vpt 1.12 mul add M + hpt neg vpt -1.62 mul V + hpt 2 mul 0 V + hpt neg vpt 1.62 mul V closepath fill} def +/TriD {stroke [] 0 setdash 2 copy vpt 1.12 mul sub M + hpt neg vpt 1.62 mul V + hpt 2 mul 0 V + hpt neg vpt -1.62 mul V closepath stroke + Pnt} def +/TriDF {stroke [] 0 setdash vpt 1.12 mul sub M + hpt neg vpt 1.62 mul V + hpt 2 mul 0 V + hpt neg vpt -1.62 mul V closepath fill} def +/DiaF {stroke [] 0 setdash vpt add M + hpt neg vpt neg V hpt vpt neg V + hpt vpt V hpt neg vpt V closepath fill} def +/Pent {stroke [] 0 setdash 2 copy gsave + translate 0 hpt M 4 {72 rotate 0 hpt L} repeat + closepath stroke grestore Pnt} def +/PentF {stroke [] 0 setdash gsave + translate 0 hpt M 4 {72 rotate 0 hpt L} repeat + closepath fill grestore} def +/Circle {stroke [] 0 setdash 2 copy + hpt 0 360 arc stroke Pnt} def +/CircleF {stroke [] 0 setdash hpt 0 360 arc fill} def +/C0 {BL [] 0 setdash 2 copy moveto vpt 90 450 arc} bind def +/C1 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 0 90 arc closepath fill + vpt 0 360 arc closepath} bind def +/C2 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 90 180 arc closepath fill + vpt 0 360 arc closepath} bind def +/C3 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 0 180 arc closepath fill + vpt 0 360 arc closepath} bind def +/C4 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 180 270 arc closepath fill + vpt 0 360 arc closepath} bind def +/C5 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 0 90 arc + 2 copy moveto + 2 copy vpt 180 270 arc closepath fill + vpt 0 360 arc} bind def +/C6 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 90 270 arc closepath fill + vpt 0 360 arc closepath} bind def +/C7 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 0 270 arc closepath fill + vpt 0 360 arc closepath} bind def +/C8 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 270 360 arc closepath fill + vpt 0 360 arc closepath} bind def +/C9 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 270 450 arc closepath fill + vpt 0 360 arc closepath} bind def +/C10 {BL [] 0 setdash 2 copy 2 copy moveto vpt 270 360 arc closepath fill + 2 copy moveto + 2 copy vpt 90 180 arc closepath fill + vpt 0 360 arc closepath} bind def +/C11 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 0 180 arc closepath fill + 2 copy moveto + 2 copy vpt 270 360 arc closepath fill + vpt 0 360 arc closepath} bind def +/C12 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 180 360 arc closepath fill + vpt 0 360 arc closepath} bind def +/C13 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 0 90 arc closepath fill + 2 copy moveto + 2 copy vpt 180 360 arc closepath fill + vpt 0 360 arc closepath} bind def +/C14 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 90 360 arc closepath fill + vpt 0 360 arc} bind def +/C15 {BL [] 0 setdash 2 copy vpt 0 360 arc closepath fill + vpt 0 360 arc closepath} bind def +/Rec {newpath 4 2 roll moveto 1 index 0 rlineto 0 exch rlineto + neg 0 rlineto closepath} bind def +/Square {dup Rec} bind def +/Bsquare {vpt sub exch vpt sub exch vpt2 Square} bind def +/S0 {BL [] 0 setdash 2 copy moveto 0 vpt rlineto BL Bsquare} bind def +/S1 {BL [] 0 setdash 2 copy vpt Square fill Bsquare} bind def +/S2 {BL [] 0 setdash 2 copy exch vpt sub exch vpt Square fill Bsquare} bind def +/S3 {BL [] 0 setdash 2 copy exch vpt sub exch vpt2 vpt Rec fill Bsquare} bind def +/S4 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt Square fill Bsquare} bind def +/S5 {BL [] 0 setdash 2 copy 2 copy vpt Square fill + exch vpt sub exch vpt sub vpt Square fill Bsquare} bind def +/S6 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt vpt2 Rec fill Bsquare} bind def +/S7 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt vpt2 Rec fill + 2 copy vpt Square fill Bsquare} bind def +/S8 {BL [] 0 setdash 2 copy vpt sub vpt Square fill Bsquare} bind def +/S9 {BL [] 0 setdash 2 copy vpt sub vpt vpt2 Rec fill Bsquare} bind def +/S10 {BL [] 0 setdash 2 copy vpt sub vpt Square fill 2 copy exch vpt sub exch vpt Square fill + Bsquare} bind def +/S11 {BL [] 0 setdash 2 copy vpt sub vpt Square fill 2 copy exch vpt sub exch vpt2 vpt Rec fill + Bsquare} bind def +/S12 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt2 vpt Rec fill Bsquare} bind def +/S13 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt2 vpt Rec fill + 2 copy vpt Square fill Bsquare} bind def +/S14 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt2 vpt Rec fill + 2 copy exch vpt sub exch vpt Square fill Bsquare} bind def +/S15 {BL [] 0 setdash 2 copy Bsquare fill Bsquare} bind def +/D0 {gsave translate 45 rotate 0 0 S0 stroke grestore} bind def +/D1 {gsave translate 45 rotate 0 0 S1 stroke grestore} bind def +/D2 {gsave translate 45 rotate 0 0 S2 stroke grestore} bind def +/D3 {gsave translate 45 rotate 0 0 S3 stroke grestore} bind def +/D4 {gsave translate 45 rotate 0 0 S4 stroke grestore} bind def +/D5 {gsave translate 45 rotate 0 0 S5 stroke grestore} bind def +/D6 {gsave translate 45 rotate 0 0 S6 stroke grestore} bind def +/D7 {gsave translate 45 rotate 0 0 S7 stroke grestore} bind def +/D8 {gsave translate 45 rotate 0 0 S8 stroke grestore} bind def +/D9 {gsave translate 45 rotate 0 0 S9 stroke grestore} bind def +/D10 {gsave translate 45 rotate 0 0 S10 stroke grestore} bind def +/D11 {gsave translate 45 rotate 0 0 S11 stroke grestore} bind def +/D12 {gsave translate 45 rotate 0 0 S12 stroke grestore} bind def +/D13 {gsave translate 45 rotate 0 0 S13 stroke grestore} bind def +/D14 {gsave translate 45 rotate 0 0 S14 stroke grestore} bind def +/D15 {gsave translate 45 rotate 0 0 S15 stroke grestore} bind def +/DiaE {stroke [] 0 setdash vpt add M + hpt neg vpt neg V hpt vpt neg V + hpt vpt V hpt neg vpt V closepath stroke} def +/BoxE {stroke [] 0 setdash exch hpt sub exch vpt add M + 0 vpt2 neg V hpt2 0 V 0 vpt2 V + hpt2 neg 0 V closepath stroke} def +/TriUE {stroke [] 0 setdash vpt 1.12 mul add M + hpt neg vpt -1.62 mul V + hpt 2 mul 0 V + hpt neg vpt 1.62 mul V closepath stroke} def +/TriDE {stroke [] 0 setdash vpt 1.12 mul sub M + hpt neg vpt 1.62 mul V + hpt 2 mul 0 V + hpt neg vpt -1.62 mul V closepath stroke} def +/PentE {stroke [] 0 setdash gsave + translate 0 hpt M 4 {72 rotate 0 hpt L} repeat + closepath stroke grestore} def +/CircE {stroke [] 0 setdash + hpt 0 360 arc stroke} def +/Opaque {gsave closepath 1 setgray fill grestore 0 setgray closepath} def +/DiaW {stroke [] 0 setdash vpt add M + hpt neg vpt neg V hpt vpt neg V + hpt vpt V hpt neg vpt V Opaque stroke} def +/BoxW {stroke [] 0 setdash exch hpt sub exch vpt add M + 0 vpt2 neg V hpt2 0 V 0 vpt2 V + hpt2 neg 0 V Opaque stroke} def +/TriUW {stroke [] 0 setdash vpt 1.12 mul add M + hpt neg vpt -1.62 mul V + hpt 2 mul 0 V + hpt neg vpt 1.62 mul V Opaque stroke} def +/TriDW {stroke [] 0 setdash vpt 1.12 mul sub M + hpt neg vpt 1.62 mul V + hpt 2 mul 0 V + hpt neg vpt -1.62 mul V Opaque stroke} def +/PentW {stroke [] 0 setdash gsave + translate 0 hpt M 4 {72 rotate 0 hpt L} repeat + Opaque stroke grestore} def +/CircW {stroke [] 0 setdash + hpt 0 360 arc Opaque stroke} def +/BoxFill {gsave Rec 1 setgray fill grestore} def +/Density { + /Fillden exch def + currentrgbcolor + /ColB exch def /ColG exch def /ColR exch def + /ColR ColR Fillden mul Fillden sub 1 add def + /ColG ColG Fillden mul Fillden sub 1 add def + /ColB ColB Fillden mul Fillden sub 1 add def + ColR ColG ColB setrgbcolor} def +/BoxColFill {gsave Rec PolyFill} def +/PolyFill {gsave Density fill grestore grestore} def +/h {rlineto rlineto rlineto gsave closepath fill grestore} bind def +% +% PostScript Level 1 Pattern Fill routine for rectangles +% Usage: x y w h s a XX PatternFill +% x,y = lower left corner of box to be filled +% w,h = width and height of box +% a = angle in degrees between lines and x-axis +% XX = 0/1 for no/yes cross-hatch +% +/PatternFill {gsave /PFa [ 9 2 roll ] def + PFa 0 get PFa 2 get 2 div add PFa 1 get PFa 3 get 2 div add translate + PFa 2 get -2 div PFa 3 get -2 div PFa 2 get PFa 3 get Rec + gsave 1 setgray fill grestore clip + currentlinewidth 0.5 mul setlinewidth + /PFs PFa 2 get dup mul PFa 3 get dup mul add sqrt def + 0 0 M PFa 5 get rotate PFs -2 div dup translate + 0 1 PFs PFa 4 get div 1 add floor cvi + {PFa 4 get mul 0 M 0 PFs V} for + 0 PFa 6 get ne { + 0 1 PFs PFa 4 get div 1 add floor cvi + {PFa 4 get mul 0 2 1 roll M PFs 0 V} for + } if + stroke grestore} def +% +/languagelevel where + {pop languagelevel} {1} ifelse + 2 lt + {/InterpretLevel1 true def} + {/InterpretLevel1 Level1 def} + ifelse +% +% PostScript level 2 pattern fill definitions +% +/Level2PatternFill { +/Tile8x8 {/PaintType 2 /PatternType 1 /TilingType 1 /BBox [0 0 8 8] /XStep 8 /YStep 8} + bind def +/KeepColor {currentrgbcolor [/Pattern /DeviceRGB] setcolorspace} bind def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 0 M 8 8 L 0 8 M 8 0 L stroke} +>> matrix makepattern +/Pat1 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 0 M 8 8 L 0 8 M 8 0 L stroke + 0 4 M 4 8 L 8 4 L 4 0 L 0 4 L stroke} +>> matrix makepattern +/Pat2 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 0 M 0 8 L + 8 8 L 8 0 L 0 0 L fill} +>> matrix makepattern +/Pat3 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -4 8 M 8 -4 L + 0 12 M 12 0 L stroke} +>> matrix makepattern +/Pat4 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -4 0 M 8 12 L + 0 -4 M 12 8 L stroke} +>> matrix makepattern +/Pat5 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -2 8 M 4 -4 L + 0 12 M 8 -4 L 4 12 M 10 0 L stroke} +>> matrix makepattern +/Pat6 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -2 0 M 4 12 L + 0 -4 M 8 12 L 4 -4 M 10 8 L stroke} +>> matrix makepattern +/Pat7 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 8 -2 M -4 4 L + 12 0 M -4 8 L 12 4 M 0 10 L stroke} +>> matrix makepattern +/Pat8 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 -2 M 12 4 L + -4 0 M 12 8 L -4 4 M 8 10 L stroke} +>> matrix makepattern +/Pat9 exch def +/Pattern1 {PatternBgnd KeepColor Pat1 setpattern} bind def +/Pattern2 {PatternBgnd KeepColor Pat2 setpattern} bind def +/Pattern3 {PatternBgnd KeepColor Pat3 setpattern} bind def +/Pattern4 {PatternBgnd KeepColor Landscape {Pat5} {Pat4} ifelse setpattern} bind def +/Pattern5 {PatternBgnd KeepColor Landscape {Pat4} {Pat5} ifelse setpattern} bind def +/Pattern6 {PatternBgnd KeepColor Landscape {Pat9} {Pat6} ifelse setpattern} bind def +/Pattern7 {PatternBgnd KeepColor Landscape {Pat8} {Pat7} ifelse setpattern} bind def +} def +% +% +%End of PostScript Level 2 code +% +/PatternBgnd { + TransparentPatterns {} {gsave 1 setgray fill grestore} ifelse +} def +% +% Substitute for Level 2 pattern fill codes with +% grayscale if Level 2 support is not selected. +% +/Level1PatternFill { +/Pattern1 {0.250 Density} bind def +/Pattern2 {0.500 Density} bind def +/Pattern3 {0.750 Density} bind def +/Pattern4 {0.125 Density} bind def +/Pattern5 {0.375 Density} bind def +/Pattern6 {0.625 Density} bind def +/Pattern7 {0.875 Density} bind def +} def +% +% Now test for support of Level 2 code +% +Level1 {Level1PatternFill} {Level2PatternFill} ifelse +% +/Symbol-Oblique /Symbol findfont [1 0 .167 1 0 0] makefont +dup length dict begin {1 index /FID eq {pop pop} {def} ifelse} forall +currentdict end definefont pop +/MFshow { + { dup 5 get 3 ge + { 5 get 3 eq {gsave} {grestore} ifelse } + {dup dup 0 get findfont exch 1 get scalefont setfont + [ currentpoint ] exch dup 2 get 0 exch R dup 5 get 2 ne {dup dup 6 + get exch 4 get {Gshow} {stringwidth pop 0 R} ifelse }if dup 5 get 0 eq + {dup 3 get {2 get neg 0 exch R pop} {pop aload pop M} ifelse} {dup 5 + get 1 eq {dup 2 get exch dup 3 get exch 6 get stringwidth pop -2 div + dup 0 R} {dup 6 get stringwidth pop -2 div 0 R 6 get + show 2 index {aload pop M neg 3 -1 roll neg R pop pop} {pop pop pop + pop aload pop M} ifelse }ifelse }ifelse } + ifelse } + forall} def +/Gswidth {dup type /stringtype eq {stringwidth} {pop (n) stringwidth} ifelse} def +/MFwidth {0 exch { dup 5 get 3 ge { 5 get 3 eq { 0 } { pop } ifelse } + {dup 3 get{dup dup 0 get findfont exch 1 get scalefont setfont + 6 get Gswidth pop add} {pop} ifelse} ifelse} forall} def +/MLshow { currentpoint stroke M + 0 exch R + Blacktext {gsave 0 setgray MFshow grestore} {MFshow} ifelse } bind def +/MRshow { currentpoint stroke M + exch dup MFwidth neg 3 -1 roll R + Blacktext {gsave 0 setgray MFshow grestore} {MFshow} ifelse } bind def +/MCshow { currentpoint stroke M + exch dup MFwidth -2 div 3 -1 roll R + Blacktext {gsave 0 setgray MFshow grestore} {MFshow} ifelse } bind def +/XYsave { [( ) 1 2 true false 3 ()] } bind def +/XYrestore { [( ) 1 2 true false 4 ()] } bind def +end +%%EndProlog +gnudict begin +gsave +doclip +50 50 translate +0.050 0.050 scale +0 setgray +newpath +(Helvetica) findfont 280 scalefont setfont +1.000 UL +LTb +1540 896 M +63 0 V +5176 0 R +-63 0 V +stroke +1372 896 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 0)] +] -93.3 MRshow +1.000 UL +LTb +1540 1372 M +63 0 V +5176 0 R +-63 0 V +stroke +1372 1372 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 50)] 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280.0 0.0 true true 0 (Frequency of Sense Confusion)] +] -93.3 MCshow +grestore +LTb +LCb setrgbcolor +4159 196 M +[ [(Helvetica) 280.0 0.0 true true 0 (Ontonote Sense Similarity)] +] -93.3 MCshow +LTb +2.000 UP +1.000 UL +LTb +% Begin plot #1 +2.000 UP +1.000 UL +LT0 +LCb setrgbcolor +5477 4500 M +[ [(Helvetica) 280.0 0.0 true true 0 (Actual \(avg\))] +] -93.3 MRshow +LT0 +5645 4500 M +798 0 V +1540 2300 M +169 -700 V +338 2008 V +2385 2324 L +338 228 V +338 -952 V +338 -142 V +338 -172 V +338 -238 V +338 505 V +338 -429 V +5089 896 L +338 0 V +338 0 V +338 0 V +338 0 V +338 0 V +1709 1600 Pls +2047 3608 Pls +2385 2324 Pls +2723 2552 Pls +3061 1600 Pls +3399 1458 Pls +3737 1286 Pls +4075 1048 Pls +4413 1553 Pls +4751 1124 Pls +5089 896 Pls +5427 896 Pls +5765 896 Pls +6103 896 Pls +6441 896 Pls +6779 896 Pls +6044 4500 Pls +% End plot #1 +% Begin plot #2 +2.000 UP +1.000 UL +LT1 +LC1 setrgbcolor +LCb setrgbcolor +5477 4220 M +[ [(Helvetica) 280.0 0.0 true true 0 (Baseline \(avg\))] +] 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a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-stkm-test.key.max.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-stkm-test.key.max.actual new file mode 100644 index 00000000..614c4b43 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-stkm-test.key.max.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 206.0 +0.02 0.0 +0.04 213.0 +0.06 300.0 +0.08 140.0 +0.1 75.0 +0.12 76.0 +0.14 0.0 +0.16 16.0 +0.18 110.0 +0.2 8.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 27.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 16.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-stkm-test.key.max.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-stkm-test.key.max.baseline new file mode 100644 index 00000000..34cea07e --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-25-stkm-test.key.max.baseline @@ -0,0 +1,51 @@ +# similarity error_count +0.0 190.2333333333346 +0.02 0.0 +0.04 355.3333333333334 +0.06 357.65000000000003 +0.08 123.70000000000002 +0.1 65.55000000000001 +0.12 20.416666666666664 +0.14 0.0 +0.16 15.133333333333331 +0.18 37.75 +0.2 1.5999999999999999 +0.22 0.8 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 13.5 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 5.333333333333332 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-cbc-test.key.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-cbc-test.key.actual new file mode 100644 index 00000000..a3e5ca46 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-cbc-test.key.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 68.0 +0.02 31.0 +0.04 145.0 +0.06 66.0 +0.08 49.0 +0.1 39.0 +0.12 26.0 +0.14 10.0 +0.16 4.0 +0.18 12.0 +0.2 7.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-cbc-test.key.avg.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-cbc-test.key.avg.actual new file mode 100644 index 00000000..a3e5ca46 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-cbc-test.key.avg.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 68.0 +0.02 31.0 +0.04 145.0 +0.06 66.0 +0.08 49.0 +0.1 39.0 +0.12 26.0 +0.14 10.0 +0.16 4.0 +0.18 12.0 +0.2 7.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-cbc-test.key.avg.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-cbc-test.key.avg.baseline new file mode 100644 index 00000000..00cb5267 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-cbc-test.key.avg.baseline @@ -0,0 +1,51 @@ +# similarity error_count +0.0 76.6666666666666 +0.02 35.75 +0.04 158.23333333333335 +0.06 85.11666666666666 +0.08 50.81666666666667 +0.1 18.200000000000003 +0.12 14.25 +0.14 7.5 +0.16 1.8333333333333333 +0.18 3.5 +0.2 5.133333333333333 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-cbc-test.key.baselines b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-cbc-test.key.baselines new file mode 100644 index 00000000..ee77c3b2 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-cbc-test.key.baselines @@ -0,0 +1,21 @@ +# similarity prob-of-confusion +0.0 0.21483375959079282 +0.02 0.09462915601023023 +0.04 0.3554987212276207 +0.06 0.2097186700767261 +0.08 0.06393861892583122 +0.1 0.01790281329923274 +0.12 0.01534526854219949 +0.14 0.0025575447570332483 +0.16 0.0076726342710997444 +0.18 0.0076726342710997444 +0.2 0.005115089514066497 +0.22 0.0025575447570332483 +0.24 0.0 +0.26 0.0 +0.28 0.0025575447570332483 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-cbc-test.key.eps 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arc stroke} def +/Opaque {gsave closepath 1 setgray fill grestore 0 setgray closepath} def +/DiaW {stroke [] 0 setdash vpt add M + hpt neg vpt neg V hpt vpt neg V + hpt vpt V hpt neg vpt V Opaque stroke} def +/BoxW {stroke [] 0 setdash exch hpt sub exch vpt add M + 0 vpt2 neg V hpt2 0 V 0 vpt2 V + hpt2 neg 0 V Opaque stroke} def +/TriUW {stroke [] 0 setdash vpt 1.12 mul add M + hpt neg vpt -1.62 mul V + hpt 2 mul 0 V + hpt neg vpt 1.62 mul V Opaque stroke} def +/TriDW {stroke [] 0 setdash vpt 1.12 mul sub M + hpt neg vpt 1.62 mul V + hpt 2 mul 0 V + hpt neg vpt -1.62 mul V Opaque stroke} def +/PentW {stroke [] 0 setdash gsave + translate 0 hpt M 4 {72 rotate 0 hpt L} repeat + Opaque stroke grestore} def +/CircW {stroke [] 0 setdash + hpt 0 360 arc Opaque stroke} def +/BoxFill {gsave Rec 1 setgray fill grestore} def +/Density { + /Fillden exch def + currentrgbcolor + /ColB exch def /ColG exch def /ColR exch def + /ColR ColR Fillden mul Fillden sub 1 add def + /ColG ColG Fillden mul Fillden sub 1 add def + /ColB ColB Fillden mul Fillden sub 1 add def + ColR ColG ColB setrgbcolor} def +/BoxColFill {gsave Rec PolyFill} def +/PolyFill {gsave Density fill grestore grestore} def +/h {rlineto rlineto rlineto gsave closepath fill grestore} bind def +% +% PostScript Level 1 Pattern Fill routine for rectangles +% Usage: x y w h s a XX PatternFill +% x,y = lower left corner of box to be filled +% w,h = width and height of box +% a = angle in degrees between lines and x-axis +% XX = 0/1 for no/yes cross-hatch +% +/PatternFill {gsave /PFa [ 9 2 roll ] def + PFa 0 get PFa 2 get 2 div add PFa 1 get PFa 3 get 2 div add translate + PFa 2 get -2 div PFa 3 get -2 div PFa 2 get PFa 3 get Rec + gsave 1 setgray fill grestore clip + currentlinewidth 0.5 mul setlinewidth + /PFs PFa 2 get dup mul PFa 3 get dup mul add sqrt def + 0 0 M PFa 5 get rotate PFs -2 div dup translate + 0 1 PFs PFa 4 get div 1 add floor cvi + {PFa 4 get mul 0 M 0 PFs V} for + 0 PFa 6 get ne { + 0 1 PFs PFa 4 get div 1 add floor cvi + {PFa 4 get mul 0 2 1 roll M PFs 0 V} for + } if + stroke grestore} def +% +/languagelevel where + {pop languagelevel} {1} ifelse + 2 lt + {/InterpretLevel1 true def} + {/InterpretLevel1 Level1 def} + ifelse +% +% PostScript level 2 pattern fill definitions +% +/Level2PatternFill { +/Tile8x8 {/PaintType 2 /PatternType 1 /TilingType 1 /BBox [0 0 8 8] /XStep 8 /YStep 8} + bind def +/KeepColor {currentrgbcolor [/Pattern /DeviceRGB] setcolorspace} bind def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 0 M 8 8 L 0 8 M 8 0 L stroke} +>> matrix makepattern +/Pat1 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 0 M 8 8 L 0 8 M 8 0 L stroke + 0 4 M 4 8 L 8 4 L 4 0 L 0 4 L stroke} +>> matrix makepattern +/Pat2 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 0 M 0 8 L + 8 8 L 8 0 L 0 0 L fill} +>> matrix makepattern +/Pat3 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -4 8 M 8 -4 L + 0 12 M 12 0 L stroke} +>> matrix makepattern +/Pat4 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -4 0 M 8 12 L + 0 -4 M 12 8 L stroke} +>> matrix makepattern +/Pat5 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -2 8 M 4 -4 L + 0 12 M 8 -4 L 4 12 M 10 0 L stroke} +>> matrix makepattern +/Pat6 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -2 0 M 4 12 L + 0 -4 M 8 12 L 4 -4 M 10 8 L stroke} +>> matrix makepattern +/Pat7 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 8 -2 M -4 4 L + 12 0 M -4 8 L 12 4 M 0 10 L stroke} +>> matrix makepattern +/Pat8 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 -2 M 12 4 L + -4 0 M 12 8 L -4 4 M 8 10 L stroke} +>> matrix makepattern +/Pat9 exch def +/Pattern1 {PatternBgnd KeepColor Pat1 setpattern} bind def +/Pattern2 {PatternBgnd KeepColor Pat2 setpattern} bind def +/Pattern3 {PatternBgnd KeepColor Pat3 setpattern} bind def +/Pattern4 {PatternBgnd KeepColor Landscape {Pat5} {Pat4} ifelse setpattern} bind def +/Pattern5 {PatternBgnd KeepColor Landscape {Pat4} {Pat5} ifelse setpattern} bind def +/Pattern6 {PatternBgnd KeepColor Landscape {Pat9} {Pat6} ifelse setpattern} bind def +/Pattern7 {PatternBgnd KeepColor Landscape {Pat8} {Pat7} ifelse setpattern} bind def +} def +% +% +%End of PostScript Level 2 code +% +/PatternBgnd { + TransparentPatterns {} {gsave 1 setgray fill grestore} ifelse +} def +% +% Substitute for Level 2 pattern fill codes with +% grayscale if Level 2 support is not selected. +% +/Level1PatternFill { +/Pattern1 {0.250 Density} bind def +/Pattern2 {0.500 Density} bind def +/Pattern3 {0.750 Density} bind def +/Pattern4 {0.125 Density} bind def +/Pattern5 {0.375 Density} bind def +/Pattern6 {0.625 Density} bind def +/Pattern7 {0.875 Density} bind def +} def +% +% Now test for support of Level 2 code +% +Level1 {Level1PatternFill} {Level2PatternFill} ifelse +% +/Symbol-Oblique /Symbol findfont [1 0 .167 1 0 0] makefont +dup length dict begin {1 index /FID eq {pop pop} {def} ifelse} forall +currentdict end definefont pop +/MFshow { + { dup 5 get 3 ge + { 5 get 3 eq {gsave} {grestore} ifelse } + {dup dup 0 get findfont exch 1 get scalefont setfont + [ currentpoint ] exch dup 2 get 0 exch R dup 5 get 2 ne {dup dup 6 + get exch 4 get {Gshow} {stringwidth pop 0 R} ifelse }if dup 5 get 0 eq + {dup 3 get {2 get neg 0 exch R pop} {pop aload pop M} ifelse} {dup 5 + get 1 eq {dup 2 get exch dup 3 get exch 6 get stringwidth pop -2 div + dup 0 R} {dup 6 get stringwidth pop -2 div 0 R 6 get + show 2 index {aload pop M neg 3 -1 roll neg R pop pop} {pop pop pop + pop aload pop M} ifelse }ifelse }ifelse } + ifelse } + forall} def +/Gswidth {dup type /stringtype eq {stringwidth} {pop (n) stringwidth} ifelse} def +/MFwidth {0 exch { dup 5 get 3 ge { 5 get 3 eq { 0 } { pop } ifelse } + {dup 3 get{dup dup 0 get findfont exch 1 get scalefont setfont + 6 get Gswidth pop add} {pop} ifelse} ifelse} forall} def +/MLshow { currentpoint stroke M + 0 exch R + Blacktext {gsave 0 setgray MFshow grestore} {MFshow} ifelse } bind def +/MRshow { currentpoint stroke M + exch dup MFwidth neg 3 -1 roll R + Blacktext {gsave 0 setgray MFshow grestore} {MFshow} ifelse } bind def +/MCshow { currentpoint stroke M + exch dup MFwidth -2 div 3 -1 roll R + Blacktext {gsave 0 setgray MFshow grestore} {MFshow} ifelse } bind def +/XYsave { [( ) 1 2 true false 3 ()] } bind def +/XYrestore { [( ) 1 2 true false 4 ()] } bind def +end +%%EndProlog +gnudict begin +gsave +doclip +50 50 translate +0.050 0.050 scale +0 setgray +newpath +(Helvetica) findfont 280 scalefont setfont +1.000 UL +LTb +1540 896 M +63 0 V +5176 0 R +-63 0 V +stroke +1372 896 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 0)] +] -93.3 MRshow +1.000 UL +LTb +1540 1372 M +63 0 V +5176 0 R +-63 0 V +stroke +1372 1372 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 20)] +] -93.3 MRshow +1.000 UL +LTb +1540 1848 M +63 0 V +5176 0 R +-63 0 V +stroke +1372 1848 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 40)] +] -93.3 MRshow +1.000 UL +LTb +1540 2324 M +63 0 V +5176 0 R +-63 0 V +stroke +1372 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Begin plot #1 +2.000 UP +2.000 UL +LT0 +LCb setrgbcolor +5477 4500 M +[ [(Helvetica) 280.0 0.0 true true 0 (Actual \(avg\))] +] -93.3 MRshow +LT0 +5645 4500 M +798 0 V +1540 2074 M +169 -440 V +338 2712 V +2385 2466 L +338 -404 V +338 -238 V +338 -309 V +338 -381 V +4075 991 L +338 191 V +338 -119 V +5089 896 L +338 0 V +338 0 V +338 0 V +338 0 V +338 0 V +1709 1634 Pls +2047 4346 Pls +2385 2466 Pls +2723 2062 Pls +3061 1824 Pls +3399 1515 Pls +3737 1134 Pls +4075 991 Pls +4413 1182 Pls +4751 1063 Pls +5089 896 Pls +5427 896 Pls +5765 896 Pls +6103 896 Pls +6441 896 Pls +6779 896 Pls +6044 4500 Pls +% End plot #1 +% Begin plot #2 +2.000 UP +2.000 UL +LT1 +LC1 setrgbcolor +LCb setrgbcolor +5477 4220 M +[ [(Helvetica) 280.0 0.0 true true 0 (Baseline \(avg\))] +] -93.3 MRshow +LT1 +LC1 setrgbcolor +5645 4220 M +798 0 V +1540 2233 M +169 -486 V +338 2914 V +2385 2921 L +338 -816 V +338 -776 V +338 -94 V +338 -161 V +4075 940 L +338 39 V +338 39 V +5089 896 L +338 0 V +338 0 V +338 0 V +338 0 V +338 0 V +1709 1747 Crs +2047 4661 Crs +2385 2921 Crs +2723 2105 Crs +3061 1329 Crs +3399 1235 Crs +3737 1074 Crs +4075 940 Crs +4413 979 Crs +4751 1018 Crs +5089 896 Crs +5427 896 Crs +5765 896 Crs +6103 896 Crs +6441 896 Crs +6779 896 Crs +6044 4220 Crs +% End plot #2 +% Begin plot #3 +2.000 UP +2.000 UL +LT0 +LC2 setrgbcolor +LCb setrgbcolor +5477 3940 M +[ [(Helvetica) 280.0 0.0 true true 0 (Actual \(max\))] +] -93.3 MRshow +LT0 +LC2 setrgbcolor +5645 3940 M +798 0 V +1540 1622 M +1709 896 L +338 2641 V +338 476 V +2723 1943 L +338 -286 V +338 -119 V +3737 896 L +338 95 V +338 428 V +4751 991 L +338 -95 V +338 0 V +338 0 V +338 0 V +338 428 V +6779 896 L +1709 896 Star +2047 3537 Star +2385 4013 Star +2723 1943 Star +3061 1657 Star +3399 1538 Star +3737 896 Star +4075 991 Star +4413 1419 Star +4751 991 Star +5089 896 Star +5427 896 Star +5765 896 Star +6103 896 Star +6441 1324 Star +6779 896 Star +6044 3940 Star +% End plot #3 +% Begin plot #4 +2.000 UP +2.000 UL +LT1 +LC3 setrgbcolor +LCb setrgbcolor +5477 3660 M +[ [(Helvetica) 280.0 0.0 true true 0 (Baseline \(max\))] +] -93.3 MRshow +LT1 +LC3 setrgbcolor +5645 3660 M +798 0 V +1540 1725 M +1709 896 L +338 3244 V +338 19 V +2723 2037 L +338 -663 V +338 -68 V +3737 896 L +338 72 V +338 190 V +4751 939 L +338 -33 V +338 -10 V +338 0 V +338 0 V +338 214 V +6779 896 L +1709 896 Box +2047 4140 Box +2385 4159 Box +2723 2037 Box +3061 1374 Box +3399 1306 Box +3737 896 Box +4075 968 Box +4413 1158 Box +4751 939 Box +5089 906 Box +5427 896 Box +5765 896 Box +6103 896 Box +6441 1110 Box +6779 896 Box +6044 3660 Box +% End plot #4 +1.000 UL +LTb +1540 4703 N +0 -3807 V +5239 0 V +0 3807 V +-5239 0 V +Z stroke +2.000 UP +1.000 UL +LTb +stroke +grestore +end +showpage +%%Trailer +%%DocumentFonts: Helvetica diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-cbc-test.key.max.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-cbc-test.key.max.actual new file mode 100644 index 00000000..b9f60eb8 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-cbc-test.key.max.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 61.0 +0.02 0.0 +0.04 111.0 +0.06 131.0 +0.08 44.0 +0.1 32.0 +0.12 27.0 +0.14 0.0 +0.16 4.0 +0.18 22.0 +0.2 4.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 18.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 3.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-cbc-test.key.max.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-cbc-test.key.max.baseline new file mode 100644 index 00000000..6e9db292 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-cbc-test.key.max.baseline @@ -0,0 +1,51 @@ +# similarity error_count +0.0 69.6666666666666 +0.02 0.0 +0.04 136.33333333333334 +0.06 137.11666666666665 +0.08 47.96666666666667 +0.1 20.1 +0.12 17.25 +0.14 0.0 +0.16 3.033333333333333 +0.18 11.0 +0.2 1.7999999999999998 +0.22 0.4 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 9.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 3.3333333333333335 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-cbc-test.key.png b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-cbc-test.key.png new file mode 100644 index 00000000..7c760a05 Binary files /dev/null and b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-cbc-test.key.png differ diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-gs-kmeans-test.key.avg.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-gs-kmeans-test.key.avg.actual new file mode 100644 index 00000000..9456cafe --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-gs-kmeans-test.key.avg.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 221.0 +0.02 74.0 +0.04 285.0 +0.06 150.0 +0.08 174.0 +0.1 74.0 +0.12 59.0 +0.14 41.0 +0.16 16.0 +0.18 69.0 +0.2 24.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-gs-kmeans-test.key.avg.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-gs-kmeans-test.key.avg.baseline new file mode 100644 index 00000000..8996b7dc --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-gs-kmeans-test.key.avg.baseline @@ -0,0 +1,51 @@ +# similarity error_count +0.0 208.2333333333346 +0.02 95.91666666666666 +0.04 361.46666666666687 +0.06 266.19999999999993 +0.08 151.96666666666667 +0.1 31.450000000000003 +0.12 14.75 +0.14 20.5 +0.16 12.333333333333332 +0.18 17.25 +0.2 6.933333333333332 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-gs-kmeans-test.key.eps b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-gs-kmeans-test.key.eps new file mode 100644 index 00000000..701440a6 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-gs-kmeans-test.key.eps @@ -0,0 +1,851 @@ +%!PS-Adobe-2.0 EPSF-2.0 +%%Title: semEval-2010-dv-wc-wordsi-gs-kmeans-test.key.eps +%%Creator: gnuplot 4.3 patchlevel 0 +%%CreationDate: Fri Jul 1 14:03:15 2011 +%%DocumentFonts: (atend) +%%BoundingBox: 50 50 410 302 +%%EndComments +%%BeginProlog +/gnudict 256 dict def +gnudict begin +% +% The following true/false flags may be edited by hand if desired. +% The unit line width and grayscale image gamma correction may also be 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#4 +1.000 UL +LTb +1540 4703 N +0 -3807 V +5239 0 V +0 3807 V +-5239 0 V +Z stroke +2.000 UP +1.000 UL +LTb +stroke +grestore +end +showpage +%%Trailer +%%DocumentFonts: Helvetica diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-gs-kmeans-test.key.max.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-gs-kmeans-test.key.max.actual new file mode 100644 index 00000000..614c4b43 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-gs-kmeans-test.key.max.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 206.0 +0.02 0.0 +0.04 213.0 +0.06 300.0 +0.08 140.0 +0.1 75.0 +0.12 76.0 +0.14 0.0 +0.16 16.0 +0.18 110.0 +0.2 8.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 27.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 16.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-gs-kmeans-test.key.max.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-gs-kmeans-test.key.max.baseline new file mode 100644 index 00000000..34cea07e --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-gs-kmeans-test.key.max.baseline @@ -0,0 +1,51 @@ +# similarity error_count +0.0 190.2333333333346 +0.02 0.0 +0.04 355.3333333333334 +0.06 357.65000000000003 +0.08 123.70000000000002 +0.1 65.55000000000001 +0.12 20.416666666666664 +0.14 0.0 +0.16 15.133333333333331 +0.18 37.75 +0.2 1.5999999999999999 +0.22 0.8 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 13.5 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 5.333333333333332 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-cbc-test.key.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-cbc-test.key.actual new file mode 100644 index 00000000..bdf8574e --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-cbc-test.key.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 18.0 +0.02 5.0 +0.04 45.0 +0.06 37.0 +0.08 20.0 +0.1 20.0 +0.12 15.0 +0.14 5.0 +0.16 5.0 +0.18 3.0 +0.2 1.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-cbc-test.key.avg.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-cbc-test.key.avg.actual new file mode 100644 index 00000000..bdf8574e --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-cbc-test.key.avg.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 18.0 +0.02 5.0 +0.04 45.0 +0.06 37.0 +0.08 20.0 +0.1 20.0 +0.12 15.0 +0.14 5.0 +0.16 5.0 +0.18 3.0 +0.2 1.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-cbc-test.key.avg.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-cbc-test.key.avg.baseline new file mode 100644 index 00000000..6a3c7124 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-cbc-test.key.avg.baseline @@ -0,0 +1,51 @@ +# similarity error_count +0.0 21.81666666666666 +0.02 9.0 +0.04 53.283333333333324 +0.06 36.300000000000004 +0.08 27.1 +0.1 7.45 +0.12 12.0 +0.14 3.0 +0.16 2.1666666666666665 +0.18 0.75 +0.2 1.1333333333333333 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-cbc-test.key.baselines b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-cbc-test.key.baselines new file mode 100644 index 00000000..ee77c3b2 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-cbc-test.key.baselines @@ -0,0 +1,21 @@ +# similarity prob-of-confusion +0.0 0.21483375959079282 +0.02 0.09462915601023023 +0.04 0.3554987212276207 +0.06 0.2097186700767261 +0.08 0.06393861892583122 +0.1 0.01790281329923274 +0.12 0.01534526854219949 +0.14 0.0025575447570332483 +0.16 0.0076726342710997444 +0.18 0.0076726342710997444 +0.2 0.005115089514066497 +0.22 0.0025575447570332483 +0.24 0.0 +0.26 0.0 +0.28 0.0025575447570332483 +0.3 0.0 +0.32 0.0 +0.34 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add M + hpt neg vpt -1.62 mul V + hpt 2 mul 0 V + hpt neg vpt 1.62 mul V closepath fill} def +/TriD {stroke [] 0 setdash 2 copy vpt 1.12 mul sub M + hpt neg vpt 1.62 mul V + hpt 2 mul 0 V + hpt neg vpt -1.62 mul V closepath stroke + Pnt} def +/TriDF {stroke [] 0 setdash vpt 1.12 mul sub M + hpt neg vpt 1.62 mul V + hpt 2 mul 0 V + hpt neg vpt -1.62 mul V closepath fill} def +/DiaF {stroke [] 0 setdash vpt add M + hpt neg vpt neg V hpt vpt neg V + hpt vpt V hpt neg vpt V closepath fill} def +/Pent {stroke [] 0 setdash 2 copy gsave + translate 0 hpt M 4 {72 rotate 0 hpt L} repeat + closepath stroke grestore Pnt} def +/PentF {stroke [] 0 setdash gsave + translate 0 hpt M 4 {72 rotate 0 hpt L} repeat + closepath fill grestore} def +/Circle {stroke [] 0 setdash 2 copy + hpt 0 360 arc stroke Pnt} def +/CircleF {stroke [] 0 setdash hpt 0 360 arc fill} def +/C0 {BL [] 0 setdash 2 copy moveto vpt 90 450 arc} bind def +/C1 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 0 90 arc closepath fill + vpt 0 360 arc closepath} bind def +/C2 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 90 180 arc closepath fill + vpt 0 360 arc closepath} bind def +/C3 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 0 180 arc closepath fill + vpt 0 360 arc closepath} bind def +/C4 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 180 270 arc closepath fill + vpt 0 360 arc closepath} bind def +/C5 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 0 90 arc + 2 copy moveto + 2 copy vpt 180 270 arc closepath fill + vpt 0 360 arc} bind def +/C6 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 90 270 arc closepath fill + vpt 0 360 arc closepath} bind def +/C7 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 0 270 arc closepath fill + vpt 0 360 arc closepath} bind def +/C8 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 270 360 arc closepath fill + vpt 0 360 arc closepath} bind def +/C9 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 270 450 arc closepath fill + vpt 0 360 arc closepath} bind def +/C10 {BL [] 0 setdash 2 copy 2 copy moveto vpt 270 360 arc closepath fill + 2 copy moveto + 2 copy vpt 90 180 arc closepath fill + vpt 0 360 arc closepath} bind def +/C11 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 0 180 arc closepath fill + 2 copy moveto + 2 copy vpt 270 360 arc closepath fill + vpt 0 360 arc closepath} bind def +/C12 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 180 360 arc closepath fill + vpt 0 360 arc closepath} bind def +/C13 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 0 90 arc closepath fill + 2 copy moveto + 2 copy vpt 180 360 arc closepath fill + vpt 0 360 arc closepath} bind def +/C14 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 90 360 arc closepath fill + vpt 0 360 arc} bind def +/C15 {BL [] 0 setdash 2 copy vpt 0 360 arc closepath fill + vpt 0 360 arc closepath} bind def +/Rec {newpath 4 2 roll moveto 1 index 0 rlineto 0 exch rlineto + neg 0 rlineto closepath} bind def +/Square {dup Rec} bind def +/Bsquare {vpt sub exch vpt sub exch vpt2 Square} bind def +/S0 {BL [] 0 setdash 2 copy moveto 0 vpt rlineto BL Bsquare} bind def +/S1 {BL [] 0 setdash 2 copy vpt Square fill Bsquare} bind def +/S2 {BL [] 0 setdash 2 copy exch vpt sub exch vpt Square fill Bsquare} bind def +/S3 {BL [] 0 setdash 2 copy exch vpt sub exch vpt2 vpt Rec fill Bsquare} bind def +/S4 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt Square fill Bsquare} bind def +/S5 {BL [] 0 setdash 2 copy 2 copy vpt Square fill + exch vpt sub exch vpt sub vpt Square fill Bsquare} bind def +/S6 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt vpt2 Rec fill Bsquare} bind def +/S7 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt vpt2 Rec fill + 2 copy vpt Square fill Bsquare} bind def +/S8 {BL [] 0 setdash 2 copy vpt sub vpt Square fill Bsquare} bind def +/S9 {BL [] 0 setdash 2 copy vpt sub vpt vpt2 Rec fill Bsquare} bind def +/S10 {BL [] 0 setdash 2 copy vpt sub vpt Square fill 2 copy exch vpt sub exch vpt Square fill + Bsquare} bind def +/S11 {BL [] 0 setdash 2 copy vpt sub vpt Square fill 2 copy exch vpt sub exch vpt2 vpt Rec fill + Bsquare} bind def +/S12 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt2 vpt Rec fill Bsquare} bind def +/S13 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt2 vpt Rec fill + 2 copy vpt Square fill Bsquare} bind def +/S14 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt2 vpt Rec fill + 2 copy exch vpt sub exch vpt Square fill Bsquare} bind def +/S15 {BL [] 0 setdash 2 copy Bsquare fill Bsquare} bind def +/D0 {gsave translate 45 rotate 0 0 S0 stroke grestore} bind def +/D1 {gsave translate 45 rotate 0 0 S1 stroke grestore} bind def +/D2 {gsave translate 45 rotate 0 0 S2 stroke grestore} bind def +/D3 {gsave translate 45 rotate 0 0 S3 stroke grestore} bind def +/D4 {gsave translate 45 rotate 0 0 S4 stroke grestore} bind def +/D5 {gsave translate 45 rotate 0 0 S5 stroke grestore} bind def +/D6 {gsave translate 45 rotate 0 0 S6 stroke grestore} bind def +/D7 {gsave translate 45 rotate 0 0 S7 stroke grestore} bind def +/D8 {gsave translate 45 rotate 0 0 S8 stroke grestore} bind def +/D9 {gsave translate 45 rotate 0 0 S9 stroke grestore} bind def +/D10 {gsave translate 45 rotate 0 0 S10 stroke grestore} bind def +/D11 {gsave translate 45 rotate 0 0 S11 stroke grestore} bind def +/D12 {gsave translate 45 rotate 0 0 S12 stroke grestore} bind def +/D13 {gsave translate 45 rotate 0 0 S13 stroke grestore} bind def +/D14 {gsave translate 45 rotate 0 0 S14 stroke grestore} bind def +/D15 {gsave translate 45 rotate 0 0 S15 stroke grestore} bind def +/DiaE {stroke [] 0 setdash vpt add M + hpt neg vpt neg V hpt vpt neg V + hpt vpt V hpt neg vpt V closepath stroke} def +/BoxE {stroke [] 0 setdash exch hpt sub exch vpt add M + 0 vpt2 neg V hpt2 0 V 0 vpt2 V + hpt2 neg 0 V closepath stroke} def +/TriUE {stroke [] 0 setdash vpt 1.12 mul add M + hpt neg vpt -1.62 mul V + hpt 2 mul 0 V + hpt neg vpt 1.62 mul V closepath stroke} def +/TriDE {stroke [] 0 setdash vpt 1.12 mul sub M + hpt neg vpt 1.62 mul V + hpt 2 mul 0 V + hpt neg vpt -1.62 mul V closepath stroke} def +/PentE {stroke [] 0 setdash gsave + translate 0 hpt M 4 {72 rotate 0 hpt L} repeat + closepath stroke grestore} def +/CircE {stroke [] 0 setdash + hpt 0 360 arc stroke} def +/Opaque {gsave closepath 1 setgray fill grestore 0 setgray closepath} def +/DiaW {stroke [] 0 setdash vpt add M + hpt neg vpt neg V hpt vpt neg V + hpt vpt V hpt neg vpt V Opaque stroke} def +/BoxW {stroke [] 0 setdash exch hpt sub exch vpt add M + 0 vpt2 neg V hpt2 0 V 0 vpt2 V + hpt2 neg 0 V Opaque stroke} def +/TriUW {stroke [] 0 setdash vpt 1.12 mul add M + hpt neg vpt -1.62 mul V + hpt 2 mul 0 V + hpt neg vpt 1.62 mul V Opaque stroke} def +/TriDW {stroke [] 0 setdash vpt 1.12 mul sub M + hpt neg vpt 1.62 mul V + hpt 2 mul 0 V + hpt neg vpt -1.62 mul V Opaque stroke} def +/PentW {stroke [] 0 setdash gsave + translate 0 hpt M 4 {72 rotate 0 hpt L} repeat + Opaque stroke grestore} def +/CircW {stroke [] 0 setdash + hpt 0 360 arc Opaque stroke} def +/BoxFill {gsave Rec 1 setgray fill grestore} def +/Density { + /Fillden exch def + currentrgbcolor + /ColB exch def /ColG exch def /ColR exch def + /ColR ColR Fillden mul Fillden sub 1 add def + /ColG ColG Fillden mul Fillden sub 1 add def + /ColB ColB Fillden mul Fillden sub 1 add def + ColR ColG ColB setrgbcolor} def +/BoxColFill {gsave Rec PolyFill} def +/PolyFill {gsave Density fill grestore grestore} def +/h {rlineto rlineto rlineto gsave closepath fill grestore} bind def +% +% PostScript Level 1 Pattern Fill routine for rectangles +% Usage: x y w h s a XX PatternFill +% x,y = lower left corner of box to be filled +% w,h = width and height of box +% a = angle in degrees between lines and x-axis +% XX = 0/1 for no/yes cross-hatch +% +/PatternFill {gsave /PFa [ 9 2 roll ] def + PFa 0 get PFa 2 get 2 div add PFa 1 get PFa 3 get 2 div add translate + PFa 2 get -2 div PFa 3 get -2 div PFa 2 get PFa 3 get Rec + gsave 1 setgray fill grestore clip + currentlinewidth 0.5 mul setlinewidth + /PFs PFa 2 get dup mul PFa 3 get dup mul add sqrt def + 0 0 M PFa 5 get rotate PFs -2 div dup translate + 0 1 PFs PFa 4 get div 1 add floor cvi + {PFa 4 get mul 0 M 0 PFs V} for + 0 PFa 6 get ne { + 0 1 PFs PFa 4 get div 1 add floor cvi + {PFa 4 get mul 0 2 1 roll M PFs 0 V} for + } if + stroke grestore} def +% +/languagelevel where + {pop languagelevel} {1} ifelse + 2 lt + {/InterpretLevel1 true def} + {/InterpretLevel1 Level1 def} + ifelse +% +% PostScript level 2 pattern fill definitions +% +/Level2PatternFill { +/Tile8x8 {/PaintType 2 /PatternType 1 /TilingType 1 /BBox [0 0 8 8] /XStep 8 /YStep 8} + bind def +/KeepColor {currentrgbcolor [/Pattern /DeviceRGB] setcolorspace} bind def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 0 M 8 8 L 0 8 M 8 0 L stroke} +>> matrix makepattern +/Pat1 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 0 M 8 8 L 0 8 M 8 0 L stroke + 0 4 M 4 8 L 8 4 L 4 0 L 0 4 L stroke} +>> matrix makepattern +/Pat2 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 0 M 0 8 L + 8 8 L 8 0 L 0 0 L fill} +>> matrix makepattern +/Pat3 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -4 8 M 8 -4 L + 0 12 M 12 0 L stroke} +>> matrix makepattern +/Pat4 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -4 0 M 8 12 L + 0 -4 M 12 8 L stroke} +>> matrix makepattern +/Pat5 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -2 8 M 4 -4 L + 0 12 M 8 -4 L 4 12 M 10 0 L stroke} +>> matrix makepattern +/Pat6 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -2 0 M 4 12 L + 0 -4 M 8 12 L 4 -4 M 10 8 L stroke} +>> matrix makepattern +/Pat7 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 8 -2 M -4 4 L + 12 0 M -4 8 L 12 4 M 0 10 L stroke} +>> matrix makepattern +/Pat8 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 -2 M 12 4 L + -4 0 M 12 8 L -4 4 M 8 10 L stroke} +>> matrix makepattern +/Pat9 exch def +/Pattern1 {PatternBgnd KeepColor Pat1 setpattern} bind def +/Pattern2 {PatternBgnd KeepColor Pat2 setpattern} bind def +/Pattern3 {PatternBgnd KeepColor Pat3 setpattern} bind def +/Pattern4 {PatternBgnd KeepColor Landscape {Pat5} {Pat4} ifelse setpattern} bind def +/Pattern5 {PatternBgnd KeepColor Landscape {Pat4} {Pat5} ifelse setpattern} bind def +/Pattern6 {PatternBgnd KeepColor Landscape {Pat9} {Pat6} ifelse setpattern} bind def +/Pattern7 {PatternBgnd KeepColor Landscape {Pat8} {Pat7} ifelse setpattern} bind def +} def +% +% +%End of PostScript Level 2 code +% +/PatternBgnd { + TransparentPatterns {} {gsave 1 setgray fill grestore} ifelse +} def +% +% Substitute for Level 2 pattern fill codes with +% grayscale if Level 2 support is not selected. +% +/Level1PatternFill { +/Pattern1 {0.250 Density} bind def +/Pattern2 {0.500 Density} bind def +/Pattern3 {0.750 Density} bind def +/Pattern4 {0.125 Density} bind def +/Pattern5 {0.375 Density} bind def +/Pattern6 {0.625 Density} bind def +/Pattern7 {0.875 Density} bind def +} def +% +% Now test for support of Level 2 code +% +Level1 {Level1PatternFill} {Level2PatternFill} ifelse +% +/Symbol-Oblique /Symbol findfont [1 0 .167 1 0 0] makefont +dup length dict begin {1 index /FID eq {pop pop} {def} ifelse} forall +currentdict end definefont pop +/MFshow { + { dup 5 get 3 ge + { 5 get 3 eq {gsave} {grestore} ifelse } + {dup dup 0 get findfont exch 1 get scalefont setfont + [ currentpoint ] exch dup 2 get 0 exch R dup 5 get 2 ne {dup dup 6 + get exch 4 get {Gshow} {stringwidth pop 0 R} ifelse }if dup 5 get 0 eq + {dup 3 get {2 get neg 0 exch R pop} {pop aload pop M} ifelse} {dup 5 + get 1 eq {dup 2 get exch dup 3 get exch 6 get stringwidth pop -2 div + dup 0 R} {dup 6 get stringwidth pop -2 div 0 R 6 get + show 2 index {aload pop M neg 3 -1 roll neg R pop pop} {pop pop pop + pop aload pop M} ifelse }ifelse }ifelse } + ifelse } + forall} def +/Gswidth {dup type /stringtype eq {stringwidth} {pop (n) stringwidth} ifelse} def +/MFwidth {0 exch { dup 5 get 3 ge { 5 get 3 eq { 0 } { pop } ifelse } + {dup 3 get{dup dup 0 get findfont exch 1 get scalefont setfont + 6 get Gswidth pop add} {pop} ifelse} ifelse} forall} def +/MLshow { currentpoint stroke M + 0 exch R + Blacktext {gsave 0 setgray MFshow grestore} {MFshow} ifelse } bind def +/MRshow { currentpoint stroke M + exch dup MFwidth neg 3 -1 roll R + Blacktext {gsave 0 setgray MFshow grestore} {MFshow} ifelse } bind def +/MCshow { currentpoint stroke M + exch dup MFwidth -2 div 3 -1 roll R + Blacktext {gsave 0 setgray MFshow grestore} {MFshow} ifelse } bind def +/XYsave { [( ) 1 2 true false 3 ()] } bind def +/XYrestore { [( ) 1 2 true false 4 ()] } bind def +end +%%EndProlog +gnudict begin +gsave +doclip +50 50 translate +0.050 0.050 scale +0 setgray +newpath +(Helvetica) findfont 280 scalefont setfont +1.000 UL +LTb +1372 896 M +63 0 V +5344 0 R +-63 0 V +stroke +1204 896 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 0)] +] -93.3 MRshow +1.000 UL +LTb +1372 1531 M +63 0 V +5344 0 R +-63 0 V +stroke +1204 1531 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 10)] +] -93.3 MRshow +1.000 UL +LTb +1372 2165 M +63 0 V +5344 0 R +-63 0 V +stroke +1204 2165 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 20)] +] -93.3 MRshow +1.000 UL +LTb +1372 2800 M +63 0 V +5344 0 R +-63 0 V +stroke +1204 2800 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 30)] +] -93.3 MRshow +1.000 UL +LTb +1372 3434 M +63 0 V +5344 0 R +-63 0 V +stroke +1204 3434 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 40)] +] -93.3 MRshow +1.000 UL +LTb +1372 4069 M +63 0 V +5344 0 R +-63 0 V +stroke +1204 4069 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 50)] +] -93.3 MRshow +1.000 UL +LTb +1372 4703 M +63 0 V +5344 0 R +-63 0 V +stroke +1204 4703 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 60)] +] -93.3 MRshow +1.000 UL +LTb +2070 896 M +0 63 V +0 3744 R +0 -63 V +stroke +2070 616 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 0.05)] +] -93.3 MCshow +1.000 UL +LTb +2942 896 M +0 63 V +0 3744 R +0 -63 V +stroke +2942 616 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 0.1)] +] -93.3 MCshow +1.000 UL +LTb +3814 896 M +0 63 V +0 3744 R +0 -63 V +stroke +3814 616 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 0.15)] +] -93.3 MCshow +1.000 UL +LTb +4686 896 M +0 63 V +0 3744 R +0 -63 V +stroke +4686 616 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 0.2)] +] -93.3 MCshow +1.000 UL +LTb +5558 896 M +0 63 V +0 3744 R +0 -63 V +stroke +5558 616 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 0.25)] +] -93.3 MCshow +1.000 UL +LTb +6430 896 M +0 63 V +0 3744 R +0 -63 V +stroke +6430 616 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 0.3)] +] -93.3 MCshow +1.000 UL +LTb +1.000 UL +LTb +1372 4703 N +0 -3807 V +5407 0 V +0 3807 V +-5407 0 V +Z stroke +LCb setrgbcolor +392 2799 M +currentpoint gsave translate -270 rotate 0 0 moveto +[ [(Helvetica) 280.0 0.0 true true 0 (Frequency of Sense Confusion)] +] -93.3 MCshow +grestore +LTb +LCb setrgbcolor +4075 196 M +[ [(Helvetica) 280.0 0.0 true true 0 (Ontonote Sense Similarity)] +] -93.3 MCshow +LTb +2.000 UP +1.000 UL +LTb +% Begin plot #1 +2.000 UP +1.000 UL +LT0 +LCb setrgbcolor +5477 4500 M +[ [(Helvetica) 280.0 0.0 true true 0 (Actual \(avg\))] +] -93.3 MRshow +LT0 +5645 4500 M +798 0 V +1372 1626 M +174 -413 V +349 2538 V +349 -507 V +2593 2165 L +349 0 V +349 -317 V +348 -635 V +349 0 V +349 -127 V +4686 959 L +349 -63 V +349 0 V +348 0 V +349 0 V +349 0 V +349 0 V +1546 1213 Pls +1895 3751 Pls +2244 3244 Pls +2593 2165 Pls +2942 2165 Pls +3291 1848 Pls +3639 1213 Pls +3988 1213 Pls +4337 1086 Pls +4686 959 Pls +5035 896 Pls +5384 896 Pls +5732 896 Pls +6081 896 Pls +6430 896 Pls +6779 896 Pls +6044 4500 Pls +% End plot #1 +% Begin plot #2 +2.000 UP +1.000 UL +LT1 +LC1 setrgbcolor +LCb setrgbcolor +5477 4220 M +[ [(Helvetica) 280.0 0.0 true true 0 (Baseline \(avg\))] +] -93.3 MRshow +LT1 +LC1 setrgbcolor +5645 4220 M +798 0 V +1372 1874 M +174 -407 V +349 2810 V +2244 3199 L +349 -584 V +2942 1369 L +349 288 V +348 -571 V +349 -53 V +349 -89 V +349 24 V +349 -72 V +349 0 V +348 0 V +349 0 V +349 0 V +349 0 V +1546 1467 Crs +1895 4277 Crs +2244 3199 Crs +2593 2615 Crs +2942 1369 Crs +3291 1657 Crs +3639 1086 Crs +3988 1033 Crs +4337 944 Crs +4686 968 Crs +5035 896 Crs +5384 896 Crs +5732 896 Crs +6081 896 Crs +6430 896 Crs +6779 896 Crs +6044 4220 Crs +% End plot #2 +% Begin plot #3 +2.000 UP +1.000 UL +LT0 +LC2 setrgbcolor +LCb setrgbcolor +5477 3940 M +[ [(Helvetica) 280.0 0.0 true true 0 (Actual \(max\))] +] -93.3 MRshow +LT0 +LC2 setrgbcolor +5645 3940 M +798 0 V +1372 1404 M +1546 896 L +349 2094 V +349 1396 V +2593 1911 L +349 127 V +349 -127 V +3639 896 L +349 317 V +349 191 V +4686 959 L +349 -63 V +349 0 V +348 0 V +349 0 V +349 381 V +6779 896 L +1546 896 Star +1895 2990 Star +2244 4386 Star +2593 1911 Star +2942 2038 Star +3291 1911 Star +3639 896 Star +3988 1213 Star +4337 1404 Star +4686 959 Star +5035 896 Star +5384 896 Star +5732 896 Star +6081 896 Star +6430 1277 Star +6779 896 Star +6044 3940 Star +% End plot #3 +% Begin plot #4 +2.000 UP +1.000 UL +LT3 +LCb setrgbcolor +5477 3660 M +[ [(Helvetica) 280.0 0.0 true true 0 (Baseline \(max\))] +] -93.3 MRshow +LT3 +5645 3660 M +798 0 V +1372 1541 M +1546 896 L +349 2856 V +349 470 V +2593 2388 L +349 -924 V +349 278 V +3639 896 L +349 163 V +349 75 V +4686 947 L +349 -51 V +349 0 V +348 0 V +349 0 V +349 190 V +6779 896 L +1546 896 Box +1895 3752 Box +2244 4222 Box +2593 2388 Box +2942 1464 Box +3291 1742 Box +3639 896 Box +3988 1059 Box +4337 1134 Box +4686 947 Box +5035 896 Box +5384 896 Box +5732 896 Box +6081 896 Box +6430 1086 Box +6779 896 Box +6044 3660 Box +% End plot #4 +1.000 UL +LTb +1372 4703 N +0 -3807 V +5407 0 V +0 3807 V +-5407 0 V +Z stroke +2.000 UP +1.000 UL +LTb +stroke +grestore +end +showpage +%%Trailer +%%DocumentFonts: Helvetica diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-cbc-test.key.max.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-cbc-test.key.max.actual new file mode 100644 index 00000000..9f980da4 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-cbc-test.key.max.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 16.0 +0.02 0.0 +0.04 33.0 +0.06 55.0 +0.08 16.0 +0.1 18.0 +0.12 16.0 +0.14 0.0 +0.16 5.0 +0.18 8.0 +0.2 1.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 6.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-cbc-test.key.max.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-cbc-test.key.max.baseline new file mode 100644 index 00000000..1c196c69 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-cbc-test.key.max.baseline @@ -0,0 +1,51 @@ +# similarity error_count +0.0 20.31666666666666 +0.02 0.0 +0.04 45.01666666666667 +0.06 52.41666666666666 +0.08 23.516666666666666 +0.1 8.95 +0.12 13.333333333333332 +0.14 0.0 +0.16 2.5666666666666664 +0.18 3.75 +0.2 0.8 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 3.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.3333333333333333 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-gs-kmeans-test.key.avg.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-gs-kmeans-test.key.avg.actual new file mode 100644 index 00000000..9456cafe --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-gs-kmeans-test.key.avg.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 221.0 +0.02 74.0 +0.04 285.0 +0.06 150.0 +0.08 174.0 +0.1 74.0 +0.12 59.0 +0.14 41.0 +0.16 16.0 +0.18 69.0 +0.2 24.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-gs-kmeans-test.key.avg.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-gs-kmeans-test.key.avg.baseline new file mode 100644 index 00000000..8996b7dc --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-gs-kmeans-test.key.avg.baseline @@ -0,0 +1,51 @@ +# similarity error_count +0.0 208.2333333333346 +0.02 95.91666666666666 +0.04 361.46666666666687 +0.06 266.19999999999993 +0.08 151.96666666666667 +0.1 31.450000000000003 +0.12 14.75 +0.14 20.5 +0.16 12.333333333333332 +0.18 17.25 +0.2 6.933333333333332 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git 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0 L fill} +>> matrix makepattern +/Pat3 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -4 8 M 8 -4 L + 0 12 M 12 0 L stroke} +>> matrix makepattern +/Pat4 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -4 0 M 8 12 L + 0 -4 M 12 8 L stroke} +>> matrix makepattern +/Pat5 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -2 8 M 4 -4 L + 0 12 M 8 -4 L 4 12 M 10 0 L stroke} +>> matrix makepattern +/Pat6 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -2 0 M 4 12 L + 0 -4 M 8 12 L 4 -4 M 10 8 L stroke} +>> matrix makepattern +/Pat7 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 8 -2 M -4 4 L + 12 0 M -4 8 L 12 4 M 0 10 L stroke} +>> matrix makepattern +/Pat8 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 -2 M 12 4 L + -4 0 M 12 8 L -4 4 M 8 10 L stroke} +>> matrix makepattern +/Pat9 exch def +/Pattern1 {PatternBgnd KeepColor Pat1 setpattern} bind def +/Pattern2 {PatternBgnd KeepColor Pat2 setpattern} bind def +/Pattern3 {PatternBgnd 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a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-gs-kmeans-test.key.max.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-gs-kmeans-test.key.max.actual new file mode 100644 index 00000000..614c4b43 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-gs-kmeans-test.key.max.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 206.0 +0.02 0.0 +0.04 213.0 +0.06 300.0 +0.08 140.0 +0.1 75.0 +0.12 76.0 +0.14 0.0 +0.16 16.0 +0.18 110.0 +0.2 8.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 27.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 16.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-gs-kmeans-test.key.max.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-gs-kmeans-test.key.max.baseline new file mode 100644 index 00000000..34cea07e --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-gs-kmeans-test.key.max.baseline @@ -0,0 +1,51 @@ +# similarity error_count +0.0 190.2333333333346 +0.02 0.0 +0.04 355.3333333333334 +0.06 357.65000000000003 +0.08 123.70000000000002 +0.1 65.55000000000001 +0.12 20.416666666666664 +0.14 0.0 +0.16 15.133333333333331 +0.18 37.75 +0.2 1.5999999999999999 +0.22 0.8 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 13.5 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 5.333333333333332 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-sc06-test.key.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-sc06-test.key.actual new file mode 100644 index 00000000..61be35bd --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-sc06-test.key.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 192.0 +0.02 50.0 +0.04 239.0 +0.06 152.0 +0.08 136.0 +0.1 73.0 +0.12 48.0 +0.14 34.0 +0.16 16.0 +0.18 57.0 +0.2 22.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-sc06-test.key.avg.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-sc06-test.key.avg.actual new file mode 100644 index 00000000..61be35bd --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-sc06-test.key.avg.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 192.0 +0.02 50.0 +0.04 239.0 +0.06 152.0 +0.08 136.0 +0.1 73.0 +0.12 48.0 +0.14 34.0 +0.16 16.0 +0.18 57.0 +0.2 22.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-sc06-test.key.avg.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-sc06-test.key.avg.baseline new file mode 100644 index 00000000..469bb0d8 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-sc06-test.key.avg.baseline @@ -0,0 +1,51 @@ +# similarity error_count +0.0 182.1833333333343 +0.02 84.16666666666667 +0.04 306.61666666666673 +0.06 211.61666666666667 +0.08 127.96666666666667 +0.1 30.700000000000003 +0.12 21.0 +0.14 23.5 +0.16 10.0 +0.18 14.25 +0.2 6.999999999999999 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-sc06-test.key.baselines b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-sc06-test.key.baselines new file mode 100644 index 00000000..ee77c3b2 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-sc06-test.key.baselines @@ -0,0 +1,21 @@ +# similarity prob-of-confusion +0.0 0.21483375959079282 +0.02 0.09462915601023023 +0.04 0.3554987212276207 +0.06 0.2097186700767261 +0.08 0.06393861892583122 +0.1 0.01790281329923274 +0.12 0.01534526854219949 +0.14 0.0025575447570332483 +0.16 0.0076726342710997444 +0.18 0.0076726342710997444 +0.2 0.005115089514066497 +0.22 0.0025575447570332483 +0.24 0.0 +0.26 0.0 +0.28 0.0025575447570332483 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 diff --git 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Rounded {1 setlinejoin 1 setlinecap} if} def +/UL {dup gnulinewidth mul /userlinewidth exch def + dup 1 lt {pop 1} if 10 mul /udl exch def} def +/PL {stroke userlinewidth setlinewidth + Rounded {1 setlinejoin 1 setlinecap} if} def +% Default Line colors +/LCw {1 1 1} def +/LCb {0 0 0} def +/LCa {0 0 0} def +/LC0 {1 0 0} def +/LC1 {0 1 0} def +/LC2 {0 0 1} def +/LC3 {1 0 1} def +/LC4 {0 1 1} def +/LC5 {1 1 0} def +/LC6 {0 0 0} def +/LC7 {1 0.3 0} def +/LC8 {0.5 0.5 0.5} def +% Default Line Types +/LTw {PL [] 1 setgray} def +/LTb {BL [] LCb DL} def +/LTa {AL [1 udl mul 2 udl mul] 0 setdash LCa setrgbcolor} def +/LT0 {PL [] LC0 DL} def +/LT1 {PL [4 dl1 2 dl2] LC1 DL} def +/LT2 {PL [2 dl1 3 dl2] LC2 DL} def +/LT3 {PL [1 dl1 1.5 dl2] LC3 DL} def +/LT4 {PL [6 dl1 2 dl2 1 dl1 2 dl2] LC4 DL} def +/LT5 {PL [3 dl1 3 dl2 1 dl1 3 dl2] LC5 DL} def +/LT6 {PL [2 dl1 2 dl2 2 dl1 6 dl2] LC6 DL} def +/LT7 {PL [1 dl1 2 dl2 6 dl1 2 dl2 1 dl1 2 dl2] LC7 DL} def +/LT8 {PL [2 dl1 2 dl2 2 dl1 2 dl2 2 dl1 2 dl2 2 dl1 4 dl2] LC8 DL} def +/Pnt {stroke [] 0 setdash gsave 1 setlinecap M 0 0 V stroke grestore} def +/Dia {stroke [] 0 setdash 2 copy vpt add M + hpt neg vpt neg V hpt vpt neg V + hpt vpt V hpt neg vpt V closepath stroke + Pnt} def +/Pls {stroke [] 0 setdash vpt sub M 0 vpt2 V + currentpoint stroke M + hpt neg vpt neg R hpt2 0 V stroke + } def +/Box {stroke [] 0 setdash 2 copy exch hpt sub exch vpt add M + 0 vpt2 neg V hpt2 0 V 0 vpt2 V + hpt2 neg 0 V closepath stroke + Pnt} def +/Crs {stroke [] 0 setdash exch hpt sub exch vpt add M + hpt2 vpt2 neg V currentpoint stroke M + hpt2 neg 0 R hpt2 vpt2 V stroke} def +/TriU {stroke [] 0 setdash 2 copy vpt 1.12 mul add M + hpt neg vpt -1.62 mul V + hpt 2 mul 0 V + hpt neg vpt 1.62 mul V closepath stroke + Pnt} def +/Star {2 copy Pls Crs} def +/BoxF {stroke [] 0 setdash exch hpt sub exch vpt add M + 0 vpt2 neg V hpt2 0 V 0 vpt2 V + hpt2 neg 0 V closepath fill} def +/TriUF {stroke [] 0 setdash vpt 1.12 mul add M + hpt neg vpt -1.62 mul V + hpt 2 mul 0 V + hpt neg vpt 1.62 mul V closepath fill} def +/TriD {stroke [] 0 setdash 2 copy vpt 1.12 mul sub M + hpt neg vpt 1.62 mul V + hpt 2 mul 0 V + hpt neg vpt -1.62 mul V closepath stroke + Pnt} def +/TriDF {stroke [] 0 setdash vpt 1.12 mul sub M + hpt neg vpt 1.62 mul V + hpt 2 mul 0 V + hpt neg vpt -1.62 mul V closepath fill} def +/DiaF {stroke [] 0 setdash vpt add M + hpt neg vpt neg V hpt vpt neg V + hpt vpt V hpt neg vpt V closepath fill} def +/Pent {stroke [] 0 setdash 2 copy gsave + translate 0 hpt M 4 {72 rotate 0 hpt L} repeat + closepath stroke grestore Pnt} def +/PentF {stroke [] 0 setdash gsave + translate 0 hpt M 4 {72 rotate 0 hpt L} repeat + closepath fill grestore} def +/Circle {stroke [] 0 setdash 2 copy + hpt 0 360 arc stroke Pnt} def +/CircleF {stroke [] 0 setdash hpt 0 360 arc fill} def +/C0 {BL [] 0 setdash 2 copy moveto vpt 90 450 arc} bind def +/C1 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 0 90 arc closepath fill + vpt 0 360 arc closepath} bind def +/C2 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 90 180 arc closepath fill + vpt 0 360 arc closepath} bind def +/C3 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 0 180 arc closepath fill + vpt 0 360 arc closepath} bind def +/C4 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 180 270 arc closepath fill + vpt 0 360 arc closepath} bind def +/C5 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 0 90 arc + 2 copy moveto + 2 copy vpt 180 270 arc closepath fill + vpt 0 360 arc} bind def +/C6 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 90 270 arc closepath fill + vpt 0 360 arc closepath} bind def +/C7 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 0 270 arc closepath fill + vpt 0 360 arc closepath} bind def +/C8 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 270 360 arc closepath fill + vpt 0 360 arc closepath} bind def +/C9 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 270 450 arc closepath fill + vpt 0 360 arc closepath} bind def +/C10 {BL [] 0 setdash 2 copy 2 copy moveto vpt 270 360 arc closepath fill + 2 copy moveto + 2 copy vpt 90 180 arc closepath fill + vpt 0 360 arc closepath} bind def +/C11 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 0 180 arc closepath fill + 2 copy moveto + 2 copy vpt 270 360 arc closepath fill + vpt 0 360 arc closepath} bind def +/C12 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 180 360 arc closepath fill + vpt 0 360 arc closepath} bind def +/C13 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 0 90 arc closepath fill + 2 copy moveto + 2 copy vpt 180 360 arc closepath fill + vpt 0 360 arc closepath} bind def +/C14 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 90 360 arc closepath fill + vpt 0 360 arc} bind def +/C15 {BL [] 0 setdash 2 copy vpt 0 360 arc closepath fill + vpt 0 360 arc closepath} bind def +/Rec {newpath 4 2 roll moveto 1 index 0 rlineto 0 exch rlineto + neg 0 rlineto closepath} bind def +/Square {dup Rec} bind def +/Bsquare {vpt sub exch vpt sub exch vpt2 Square} bind def +/S0 {BL [] 0 setdash 2 copy moveto 0 vpt rlineto BL Bsquare} bind def +/S1 {BL [] 0 setdash 2 copy vpt Square fill Bsquare} bind def +/S2 {BL [] 0 setdash 2 copy exch vpt sub exch vpt Square fill Bsquare} bind def +/S3 {BL [] 0 setdash 2 copy exch vpt sub exch vpt2 vpt Rec fill Bsquare} bind def +/S4 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt Square fill Bsquare} bind def +/S5 {BL [] 0 setdash 2 copy 2 copy vpt Square fill + exch vpt sub exch vpt sub vpt Square fill Bsquare} bind def +/S6 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt vpt2 Rec fill Bsquare} bind def +/S7 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt vpt2 Rec fill + 2 copy vpt Square fill Bsquare} bind def +/S8 {BL [] 0 setdash 2 copy vpt sub vpt Square fill Bsquare} bind def +/S9 {BL [] 0 setdash 2 copy vpt sub vpt vpt2 Rec fill Bsquare} bind def +/S10 {BL [] 0 setdash 2 copy vpt sub vpt Square fill 2 copy exch vpt sub exch vpt Square fill + Bsquare} bind def +/S11 {BL [] 0 setdash 2 copy vpt sub vpt Square fill 2 copy exch vpt sub exch vpt2 vpt Rec fill + Bsquare} bind def +/S12 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt2 vpt Rec fill Bsquare} bind def +/S13 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt2 vpt Rec fill + 2 copy vpt Square fill Bsquare} bind def +/S14 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt2 vpt Rec fill + 2 copy exch vpt sub exch vpt Square fill Bsquare} bind def +/S15 {BL [] 0 setdash 2 copy Bsquare fill Bsquare} bind def +/D0 {gsave translate 45 rotate 0 0 S0 stroke grestore} bind def +/D1 {gsave translate 45 rotate 0 0 S1 stroke grestore} bind def +/D2 {gsave translate 45 rotate 0 0 S2 stroke grestore} bind def +/D3 {gsave translate 45 rotate 0 0 S3 stroke grestore} bind def +/D4 {gsave translate 45 rotate 0 0 S4 stroke grestore} bind def +/D5 {gsave translate 45 rotate 0 0 S5 stroke grestore} bind def +/D6 {gsave translate 45 rotate 0 0 S6 stroke grestore} bind def +/D7 {gsave translate 45 rotate 0 0 S7 stroke grestore} bind def +/D8 {gsave translate 45 rotate 0 0 S8 stroke grestore} bind def +/D9 {gsave translate 45 rotate 0 0 S9 stroke grestore} bind def +/D10 {gsave translate 45 rotate 0 0 S10 stroke grestore} bind def +/D11 {gsave translate 45 rotate 0 0 S11 stroke grestore} bind def +/D12 {gsave translate 45 rotate 0 0 S12 stroke grestore} bind def +/D13 {gsave translate 45 rotate 0 0 S13 stroke grestore} bind def +/D14 {gsave translate 45 rotate 0 0 S14 stroke grestore} bind def +/D15 {gsave translate 45 rotate 0 0 S15 stroke grestore} bind def +/DiaE {stroke [] 0 setdash vpt add M + hpt neg vpt neg V hpt vpt neg V + hpt vpt V hpt neg vpt V closepath stroke} def +/BoxE {stroke [] 0 setdash exch hpt sub exch vpt add M + 0 vpt2 neg V hpt2 0 V 0 vpt2 V + hpt2 neg 0 V closepath stroke} def +/TriUE {stroke [] 0 setdash vpt 1.12 mul add M + hpt neg vpt -1.62 mul V + hpt 2 mul 0 V + hpt neg vpt 1.62 mul V closepath stroke} def +/TriDE {stroke [] 0 setdash vpt 1.12 mul sub M + hpt neg vpt 1.62 mul V + hpt 2 mul 0 V + hpt neg vpt -1.62 mul V closepath stroke} def +/PentE {stroke [] 0 setdash gsave + translate 0 hpt M 4 {72 rotate 0 hpt L} repeat + closepath stroke grestore} def +/CircE {stroke [] 0 setdash + hpt 0 360 arc stroke} def +/Opaque {gsave closepath 1 setgray fill grestore 0 setgray closepath} def +/DiaW {stroke [] 0 setdash vpt add M + hpt neg vpt neg V hpt vpt neg V + hpt vpt V hpt neg vpt V Opaque stroke} def +/BoxW {stroke [] 0 setdash exch hpt sub exch vpt add M + 0 vpt2 neg V hpt2 0 V 0 vpt2 V + hpt2 neg 0 V Opaque stroke} def +/TriUW {stroke [] 0 setdash vpt 1.12 mul add M + hpt neg vpt -1.62 mul V + hpt 2 mul 0 V + hpt neg vpt 1.62 mul V Opaque stroke} def +/TriDW {stroke [] 0 setdash vpt 1.12 mul sub M + hpt neg vpt 1.62 mul V + hpt 2 mul 0 V + hpt neg vpt -1.62 mul V Opaque stroke} def +/PentW {stroke [] 0 setdash gsave + translate 0 hpt M 4 {72 rotate 0 hpt L} repeat + Opaque stroke grestore} def +/CircW {stroke [] 0 setdash + hpt 0 360 arc Opaque stroke} def +/BoxFill {gsave Rec 1 setgray fill grestore} def +/Density { + /Fillden exch def + currentrgbcolor + /ColB exch def /ColG exch def /ColR exch def + /ColR ColR Fillden mul Fillden sub 1 add def + /ColG ColG Fillden mul Fillden sub 1 add def + /ColB ColB Fillden mul Fillden sub 1 add def + ColR ColG ColB setrgbcolor} def +/BoxColFill {gsave Rec PolyFill} def +/PolyFill {gsave Density fill grestore grestore} def +/h {rlineto rlineto rlineto gsave closepath fill grestore} bind def +% +% PostScript Level 1 Pattern Fill routine for rectangles +% Usage: x y w h s a XX PatternFill +% x,y = lower left corner of box to be filled +% w,h = width and height of box +% a = angle in degrees between lines and x-axis +% XX = 0/1 for no/yes cross-hatch +% +/PatternFill {gsave /PFa [ 9 2 roll ] def + PFa 0 get PFa 2 get 2 div add PFa 1 get PFa 3 get 2 div add translate + PFa 2 get -2 div PFa 3 get -2 div PFa 2 get PFa 3 get Rec + gsave 1 setgray fill grestore clip + currentlinewidth 0.5 mul setlinewidth + /PFs PFa 2 get dup mul PFa 3 get dup mul add sqrt def + 0 0 M PFa 5 get rotate PFs -2 div dup translate + 0 1 PFs PFa 4 get div 1 add floor cvi + {PFa 4 get mul 0 M 0 PFs V} for + 0 PFa 6 get ne { + 0 1 PFs PFa 4 get div 1 add floor cvi + {PFa 4 get mul 0 2 1 roll M PFs 0 V} for + } if + stroke grestore} def +% +/languagelevel where + {pop languagelevel} {1} ifelse + 2 lt + {/InterpretLevel1 true def} + {/InterpretLevel1 Level1 def} + ifelse +% +% PostScript level 2 pattern fill definitions +% +/Level2PatternFill { +/Tile8x8 {/PaintType 2 /PatternType 1 /TilingType 1 /BBox [0 0 8 8] /XStep 8 /YStep 8} + bind def +/KeepColor {currentrgbcolor [/Pattern /DeviceRGB] setcolorspace} bind def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 0 M 8 8 L 0 8 M 8 0 L stroke} +>> matrix makepattern +/Pat1 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 0 M 8 8 L 0 8 M 8 0 L stroke + 0 4 M 4 8 L 8 4 L 4 0 L 0 4 L stroke} +>> matrix makepattern +/Pat2 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 0 M 0 8 L + 8 8 L 8 0 L 0 0 L fill} +>> matrix makepattern +/Pat3 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -4 8 M 8 -4 L + 0 12 M 12 0 L stroke} +>> matrix makepattern +/Pat4 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -4 0 M 8 12 L + 0 -4 M 12 8 L stroke} +>> matrix makepattern +/Pat5 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -2 8 M 4 -4 L + 0 12 M 8 -4 L 4 12 M 10 0 L stroke} +>> matrix makepattern +/Pat6 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -2 0 M 4 12 L + 0 -4 M 8 12 L 4 -4 M 10 8 L stroke} +>> matrix makepattern +/Pat7 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 8 -2 M -4 4 L + 12 0 M -4 8 L 12 4 M 0 10 L stroke} +>> matrix makepattern +/Pat8 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 -2 M 12 4 L + -4 0 M 12 8 L -4 4 M 8 10 L stroke} +>> matrix makepattern +/Pat9 exch def +/Pattern1 {PatternBgnd KeepColor Pat1 setpattern} bind def +/Pattern2 {PatternBgnd KeepColor Pat2 setpattern} bind def +/Pattern3 {PatternBgnd KeepColor Pat3 setpattern} bind def +/Pattern4 {PatternBgnd KeepColor Landscape {Pat5} {Pat4} ifelse setpattern} bind def +/Pattern5 {PatternBgnd KeepColor Landscape {Pat4} {Pat5} ifelse setpattern} bind def +/Pattern6 {PatternBgnd KeepColor Landscape {Pat9} {Pat6} ifelse setpattern} bind def +/Pattern7 {PatternBgnd KeepColor Landscape {Pat8} {Pat7} ifelse setpattern} bind def +} def +% +% +%End of PostScript Level 2 code +% +/PatternBgnd { + TransparentPatterns {} {gsave 1 setgray fill grestore} ifelse +} def +% +% Substitute for Level 2 pattern fill codes with +% grayscale if Level 2 support is not selected. +% +/Level1PatternFill { +/Pattern1 {0.250 Density} bind def +/Pattern2 {0.500 Density} bind def +/Pattern3 {0.750 Density} bind def +/Pattern4 {0.125 Density} bind def +/Pattern5 {0.375 Density} bind def +/Pattern6 {0.625 Density} bind def +/Pattern7 {0.875 Density} bind def +} def +% +% Now test for support of Level 2 code +% +Level1 {Level1PatternFill} {Level2PatternFill} ifelse +% +/Symbol-Oblique /Symbol findfont [1 0 .167 1 0 0] makefont +dup length dict begin {1 index /FID eq {pop pop} {def} ifelse} forall +currentdict end definefont pop +/MFshow { + { dup 5 get 3 ge + { 5 get 3 eq {gsave} {grestore} ifelse } + {dup dup 0 get findfont exch 1 get scalefont setfont + [ currentpoint ] exch dup 2 get 0 exch R dup 5 get 2 ne {dup dup 6 + get exch 4 get {Gshow} {stringwidth pop 0 R} ifelse }if dup 5 get 0 eq + {dup 3 get {2 get neg 0 exch R pop} {pop aload pop M} ifelse} {dup 5 + get 1 eq {dup 2 get exch dup 3 get exch 6 get stringwidth pop -2 div + dup 0 R} {dup 6 get stringwidth pop -2 div 0 R 6 get + show 2 index {aload pop M neg 3 -1 roll neg R pop pop} {pop pop pop + pop aload pop M} ifelse }ifelse }ifelse } + ifelse } + forall} def +/Gswidth {dup type /stringtype eq {stringwidth} {pop (n) stringwidth} ifelse} def +/MFwidth {0 exch { dup 5 get 3 ge { 5 get 3 eq { 0 } { pop } ifelse } + {dup 3 get{dup dup 0 get findfont exch 1 get scalefont setfont + 6 get Gswidth pop add} {pop} ifelse} ifelse} forall} def +/MLshow { currentpoint stroke M + 0 exch R + Blacktext {gsave 0 setgray MFshow grestore} {MFshow} ifelse } bind def +/MRshow { currentpoint stroke M + exch dup MFwidth neg 3 -1 roll R + Blacktext {gsave 0 setgray MFshow grestore} {MFshow} ifelse } bind def +/MCshow { currentpoint stroke M + exch dup MFwidth -2 div 3 -1 roll R + Blacktext {gsave 0 setgray MFshow grestore} {MFshow} ifelse } bind def +/XYsave { [( ) 1 2 true false 3 ()] } bind def +/XYrestore { [( ) 1 2 true false 4 ()] } bind def +end +%%EndProlog +gnudict begin +gsave +doclip +50 50 translate +0.050 0.050 scale +0 setgray +newpath +(Helvetica) findfont 280 scalefont setfont +1.000 UL +LTb +1540 896 M +63 0 V +5176 0 R +-63 0 V +stroke +1372 896 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 0)] +] -93.3 MRshow +1.000 UL +LTb +1540 1440 M +63 0 V +5176 0 R +-63 0 V +stroke +1372 1440 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 50)] +] -93.3 MRshow +1.000 UL +LTb +1540 1984 M +63 0 V +5176 0 R +-63 0 V +stroke +1372 1984 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 100)] +] -93.3 MRshow +1.000 UL +LTb +1540 2528 M +63 0 V +5176 0 R +-63 0 V +stroke +1372 2528 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 150)] +] -93.3 MRshow +1.000 UL +LTb +1540 3071 M +63 0 V +5176 0 R +-63 0 V +stroke +1372 3071 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 200)] +] -93.3 MRshow +1.000 UL +LTb +1540 3615 M +63 0 V +5176 0 R +-63 0 V +stroke +1372 3615 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 250)] +] -93.3 MRshow +1.000 UL +LTb +1540 4159 M +63 0 V +5176 0 R +-63 0 V +stroke +1372 4159 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 300)] +] -93.3 MRshow +1.000 UL +LTb +1540 4703 M +63 0 V +5176 0 R +-63 0 V +stroke +1372 4703 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 350)] +] -93.3 MRshow +1.000 UL +LTb +2216 896 M +0 63 V +0 3744 R +0 -63 V +stroke +2216 616 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 0.05)] +] -93.3 MCshow +1.000 UL +LTb +3061 896 M +0 63 V +0 3744 R +0 -63 V +stroke +3061 616 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 0.1)] +] -93.3 MCshow +1.000 UL +LTb +3906 896 M +0 63 V +0 3744 R +0 -63 V +stroke +3906 616 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 0.15)] +] -93.3 MCshow +1.000 UL +LTb +4751 896 M +0 63 V +0 3744 R +0 -63 V +stroke +4751 616 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 0.2)] +] -93.3 MCshow +1.000 UL +LTb +5596 896 M +0 63 V +0 3744 R +0 -63 V +stroke +5596 616 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 0.25)] +] -93.3 MCshow +1.000 UL +LTb +6441 896 M +0 63 V +0 3744 R +0 -63 V +stroke +6441 616 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 0.3)] +] -93.3 MCshow +1.000 UL +LTb +1.000 UL +LTb +1540 4703 N +0 -3807 V +5239 0 V +0 3807 V +-5239 0 V +Z stroke +LCb setrgbcolor +392 2799 M +currentpoint gsave translate -270 rotate 0 0 moveto +[ [(Helvetica) 280.0 0.0 true true 0 (Frequency of Sense Confusion)] +] -93.3 MCshow +grestore +LTb +LCb setrgbcolor +4159 196 M +[ [(Helvetica) 280.0 0.0 true true 0 (Ontonote Sense Similarity)] +] -93.3 MCshow +LTb +2.000 UP +1.000 UL +LTb +% Begin plot #1 +2.000 UP +1.000 UL +LT0 +LCb setrgbcolor +5477 4500 M +[ [(Helvetica) 280.0 0.0 true true 0 (Actual \(avg\))] +] -93.3 MRshow +LT0 +5645 4500 M +798 0 V +1540 2212 M +169 -772 V +338 2056 V +338 -947 V +338 -174 V +338 -685 V +338 -272 V +338 -152 V +338 -196 V +338 446 V +338 -381 V +5089 896 L +338 0 V +338 0 V +338 0 V +338 0 V +338 0 V +1709 1440 Pls +2047 3496 Pls +2385 2549 Pls +2723 2375 Pls +3061 1690 Pls +3399 1418 Pls +3737 1266 Pls +4075 1070 Pls +4413 1516 Pls +4751 1135 Pls +5089 896 Pls +5427 896 Pls +5765 896 Pls +6103 896 Pls +6441 896 Pls +6779 896 Pls +6044 4500 Pls +% End plot #1 +% Begin plot #2 +2.000 UP +1.000 UL +LT1 +LC1 setrgbcolor +LCb setrgbcolor +5477 4220 M +[ [(Helvetica) 280.0 0.0 true true 0 (Baseline \(avg\))] +] -93.3 MRshow +LT1 +LC1 setrgbcolor +5645 4220 M +798 0 V +1540 2345 M +169 -534 V +338 2420 V +2385 3198 L +338 -910 V +3061 1230 L +338 -106 V +338 28 V +338 -147 V +338 46 V +338 -79 V +338 -76 V +338 0 V +338 0 V +338 0 V +338 0 V +338 0 V +1709 1811 Crs +2047 4231 Crs +2385 3198 Crs +2723 2288 Crs +3061 1230 Crs +3399 1124 Crs +3737 1152 Crs +4075 1005 Crs +4413 1051 Crs +4751 972 Crs +5089 896 Crs +5427 896 Crs +5765 896 Crs +6103 896 Crs +6441 896 Crs +6779 896 Crs +6044 4220 Crs +% End plot #2 +% Begin plot #3 +2.000 UP +1.000 UL +LT0 +LC2 setrgbcolor +LCb setrgbcolor +5477 3940 M +[ [(Helvetica) 280.0 0.0 true true 0 (Actual \(max\))] +] -93.3 MRshow +LT0 +LC2 setrgbcolor +5645 3940 M +798 0 V +1540 1859 M +1709 896 L +338 1773 V +338 1218 V +2723 2299 L +338 -729 V +338 -54 V +3737 896 L +338 174 V +338 816 V +4751 972 L +338 -76 V +338 0 V +338 0 V +338 0 V +338 294 V +6779 896 L +1709 896 Star +2047 2669 Star +2385 3887 Star +2723 2299 Star +3061 1570 Star +3399 1516 Star +3737 896 Star +4075 1070 Star +4413 1886 Star +4751 972 Star +5089 896 Star +5427 896 Star +5765 896 Star +6103 896 Star +6441 1190 Star +6779 896 Star +6044 3940 Star +% End plot #3 +% Begin plot #4 +2.000 UP +1.000 UL +LT3 +LCb setrgbcolor +5477 3660 M +[ [(Helvetica) 280.0 0.0 true true 0 (Baseline \(max\))] +] -93.3 MRshow +LT3 +5645 3660 M +798 0 V +1540 1794 M +1709 896 L +338 3285 V +338 -52 V +2723 2064 L +338 -635 V +338 -247 V +3737 896 L +338 139 V +338 272 V +4751 918 L +338 -13 V +338 -9 V +338 0 V +338 0 V +338 147 V +6779 896 L +1709 896 Box +2047 4181 Box +2385 4129 Box +2723 2064 Box +3061 1429 Box +3399 1182 Box +3737 896 Box +4075 1035 Box +4413 1307 Box +4751 918 Box +5089 905 Box +5427 896 Box +5765 896 Box +6103 896 Box +6441 1043 Box +6779 896 Box +6044 3660 Box +% End plot #4 +1.000 UL +LTb +1540 4703 N +0 -3807 V +5239 0 V +0 3807 V +-5239 0 V +Z stroke +2.000 UP +1.000 UL +LTb +stroke +grestore +end +showpage +%%Trailer +%%DocumentFonts: Helvetica diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-sc06-test.key.max.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-sc06-test.key.max.actual new file mode 100644 index 00000000..69009863 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-sc06-test.key.max.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 177.0 +0.02 0.0 +0.04 163.0 +0.06 275.0 +0.08 129.0 +0.1 62.0 +0.12 57.0 +0.14 0.0 +0.16 16.0 +0.18 91.0 +0.2 7.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 27.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 15.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-sc06-test.key.max.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-sc06-test.key.max.baseline new file mode 100644 index 00000000..adbb338f --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-sc06-test.key.max.baseline @@ -0,0 +1,51 @@ +# similarity error_count +0.0 165.1833333333343 +0.02 0.0 +0.04 302.05000000000007 +0.06 297.21666666666675 +0.08 107.36666666666666 +0.1 49.0 +0.12 26.333333333333332 +0.14 0.0 +0.16 12.799999999999999 +0.18 37.75 +0.2 1.9999999999999998 +0.22 0.8 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 13.5 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 4.999999999999999 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-stkm-test.key.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-stkm-test.key.actual new file mode 100644 index 00000000..5a135f47 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-stkm-test.key.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 186.0 +0.02 53.0 +0.04 208.0 +0.06 134.0 +0.08 164.0 +0.1 72.0 +0.12 59.0 +0.14 37.0 +0.16 16.0 +0.18 45.0 +0.2 13.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-stkm-test.key.avg.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-stkm-test.key.avg.actual new file mode 100644 index 00000000..5a135f47 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-stkm-test.key.avg.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 186.0 +0.02 53.0 +0.04 208.0 +0.06 134.0 +0.08 164.0 +0.1 72.0 +0.12 59.0 +0.14 37.0 +0.16 16.0 +0.18 45.0 +0.2 13.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-stkm-test.key.avg.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-stkm-test.key.avg.baseline new file mode 100644 index 00000000..56dc2604 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-stkm-test.key.avg.baseline @@ -0,0 +1,51 @@ +# similarity error_count +0.0 166.9333333333342 +0.02 82.58333333333333 +0.04 275.78333333333336 +0.06 229.78333333333333 +0.08 145.03333333333333 +0.1 30.450000000000003 +0.12 14.75 +0.14 18.5 +0.16 7.833333333333332 +0.18 11.75 +0.2 3.5999999999999996 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-stkm-test.key.baselines b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-stkm-test.key.baselines new file mode 100644 index 00000000..ee77c3b2 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-stkm-test.key.baselines @@ -0,0 +1,21 @@ +# similarity prob-of-confusion +0.0 0.21483375959079282 +0.02 0.09462915601023023 +0.04 0.3554987212276207 +0.06 0.2097186700767261 +0.08 0.06393861892583122 +0.1 0.01790281329923274 +0.12 0.01534526854219949 +0.14 0.0025575447570332483 +0.16 0.0076726342710997444 +0.18 0.0076726342710997444 +0.2 0.005115089514066497 +0.22 0.0025575447570332483 +0.24 0.0 +0.26 0.0 +0.28 0.0025575447570332483 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-stkm-test.key.eps 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-93.3 MRshow +LT3 +5645 3660 M +798 0 V +1540 1755 M +1709 896 L +338 2868 V +338 514 V +2723 2148 L +338 -590 V +338 -436 V +3737 896 L +338 116 V +338 213 V +4751 913 L +338 -8 V +338 -9 V +338 0 V +338 0 V +338 136 V +6779 896 L +1709 896 Box +2047 3764 Box +2385 4278 Box +2723 2148 Box +3061 1558 Box +3399 1122 Box +3737 896 Box +4075 1012 Box +4413 1225 Box +4751 913 Box +5089 905 Box +5427 896 Box +5765 896 Box +6103 896 Box +6441 1032 Box +6779 896 Box +6044 3660 Box +% End plot #4 +1.000 UL +LTb +1540 4703 N +0 -3807 V +5239 0 V +0 3807 V +-5239 0 V +Z stroke +2.000 UP +1.000 UL +LTb +stroke +grestore +end +showpage +%%Trailer +%%DocumentFonts: Helvetica diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-stkm-test.key.max.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-stkm-test.key.max.actual new file mode 100644 index 00000000..09fc23c2 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-stkm-test.key.max.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 175.0 +0.02 0.0 +0.04 173.0 +0.06 218.0 +0.08 142.0 +0.1 81.0 +0.12 62.0 +0.14 0.0 +0.16 16.0 +0.18 82.0 +0.2 8.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 25.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 5.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-stkm-test.key.max.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-stkm-test.key.max.baseline new file mode 100644 index 00000000..d4bee32c --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-order-stkm-test.key.max.baseline @@ -0,0 +1,51 @@ +# similarity error_count +0.0 157.9333333333342 +0.02 0.0 +0.04 263.65 +0.06 310.93333333333334 +0.08 115.10000000000001 +0.1 60.85000000000001 +0.12 20.75 +0.14 0.0 +0.16 10.633333333333333 +0.18 30.25 +0.2 1.5999999999999999 +0.22 0.8 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 12.5 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 1.9999999999999998 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-cbc-test.key.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-cbc-test.key.actual new file mode 100644 index 00000000..2956ba09 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-cbc-test.key.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 56.0 +0.02 27.0 +0.04 131.0 +0.06 72.0 +0.08 53.0 +0.1 44.0 +0.12 25.0 +0.14 8.0 +0.16 16.0 +0.18 14.0 +0.2 5.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-cbc-test.key.avg.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-cbc-test.key.avg.actual new file mode 100644 index 00000000..2956ba09 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-cbc-test.key.avg.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 56.0 +0.02 27.0 +0.04 131.0 +0.06 72.0 +0.08 53.0 +0.1 44.0 +0.12 25.0 +0.14 8.0 +0.16 16.0 +0.18 14.0 +0.2 5.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-cbc-test.key.avg.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-cbc-test.key.avg.baseline new file mode 100644 index 00000000..fe458486 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-cbc-test.key.avg.baseline @@ -0,0 +1,51 @@ +# similarity error_count +0.0 66.68333333333334 +0.02 35.25 +0.04 151.51666666666665 +0.06 85.91666666666669 +0.08 56.15 +0.1 20.85 +0.12 15.5 +0.14 7.0 +0.16 5.333333333333332 +0.18 4.0 +0.2 2.8 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-cbc-test.key.baselines b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-cbc-test.key.baselines new file mode 100644 index 00000000..ee77c3b2 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-cbc-test.key.baselines @@ -0,0 +1,21 @@ +# similarity prob-of-confusion +0.0 0.21483375959079282 +0.02 0.09462915601023023 +0.04 0.3554987212276207 +0.06 0.2097186700767261 +0.08 0.06393861892583122 +0.1 0.01790281329923274 +0.12 0.01534526854219949 +0.14 0.0025575447570332483 +0.16 0.0076726342710997444 +0.18 0.0076726342710997444 +0.2 0.005115089514066497 +0.22 0.0025575447570332483 +0.24 0.0 +0.26 0.0 +0.28 0.0025575447570332483 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-cbc-test.key.eps b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-cbc-test.key.eps new file mode 100644 index 00000000..d8617291 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-cbc-test.key.eps @@ -0,0 +1,849 @@ +%!PS-Adobe-2.0 EPSF-2.0 +%%Title: 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+0.18 22.0 +0.2 3.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 20.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 2.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-cbc-test.key.max.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-cbc-test.key.max.baseline new file mode 100644 index 00000000..568daa8c --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-cbc-test.key.max.baseline @@ -0,0 +1,51 @@ +# similarity error_count +0.0 62.68333333333334 +0.02 0.0 +0.04 138.46666666666667 +0.06 133.2166666666667 +0.08 49.150000000000006 +0.1 18.45 +0.12 19.5 +0.14 0.0 +0.16 5.7333333333333325 +0.18 11.0 +0.2 0.8 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 10.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 1.9999999999999998 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-cbc-test.key.png b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-cbc-test.key.png new file mode 100644 index 00000000..f0efcb1f Binary files /dev/null and b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-cbc-test.key.png differ diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-gs-kmeans-test.key.avg.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-gs-kmeans-test.key.avg.actual new file mode 100644 index 00000000..9456cafe --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-gs-kmeans-test.key.avg.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 221.0 +0.02 74.0 +0.04 285.0 +0.06 150.0 +0.08 174.0 +0.1 74.0 +0.12 59.0 +0.14 41.0 +0.16 16.0 +0.18 69.0 +0.2 24.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-gs-kmeans-test.key.avg.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-gs-kmeans-test.key.avg.baseline new file mode 100644 index 00000000..8996b7dc --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-gs-kmeans-test.key.avg.baseline @@ -0,0 +1,51 @@ +# similarity error_count +0.0 208.2333333333346 +0.02 95.91666666666666 +0.04 361.46666666666687 +0.06 266.19999999999993 +0.08 151.96666666666667 +0.1 31.450000000000003 +0.12 14.75 +0.14 20.5 +0.16 12.333333333333332 +0.18 17.25 +0.2 6.933333333333332 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git 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vpt Rec fill + Bsquare} bind def +/S12 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt2 vpt Rec fill Bsquare} bind def +/S13 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt2 vpt Rec fill + 2 copy vpt Square fill Bsquare} bind def +/S14 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt2 vpt Rec fill + 2 copy exch vpt sub exch vpt Square fill Bsquare} bind def +/S15 {BL [] 0 setdash 2 copy Bsquare fill Bsquare} bind def +/D0 {gsave translate 45 rotate 0 0 S0 stroke grestore} bind def +/D1 {gsave translate 45 rotate 0 0 S1 stroke grestore} bind def +/D2 {gsave translate 45 rotate 0 0 S2 stroke grestore} bind def +/D3 {gsave translate 45 rotate 0 0 S3 stroke grestore} bind def +/D4 {gsave translate 45 rotate 0 0 S4 stroke grestore} bind def +/D5 {gsave translate 45 rotate 0 0 S5 stroke grestore} bind def +/D6 {gsave translate 45 rotate 0 0 S6 stroke grestore} bind def +/D7 {gsave translate 45 rotate 0 0 S7 stroke grestore} bind def +/D8 {gsave translate 45 rotate 0 0 S8 stroke grestore} bind def +/D9 {gsave translate 45 rotate 0 0 S9 stroke grestore} bind def +/D10 {gsave translate 45 rotate 0 0 S10 stroke grestore} bind def +/D11 {gsave translate 45 rotate 0 0 S11 stroke grestore} bind def +/D12 {gsave translate 45 rotate 0 0 S12 stroke grestore} bind def +/D13 {gsave translate 45 rotate 0 0 S13 stroke grestore} bind def +/D14 {gsave translate 45 rotate 0 0 S14 stroke grestore} bind def +/D15 {gsave translate 45 rotate 0 0 S15 stroke grestore} bind def +/DiaE {stroke [] 0 setdash vpt add M + hpt neg vpt neg V hpt vpt neg V + hpt vpt V hpt neg vpt V closepath stroke} def +/BoxE {stroke [] 0 setdash exch hpt sub exch vpt add M + 0 vpt2 neg V hpt2 0 V 0 vpt2 V + hpt2 neg 0 V closepath stroke} def +/TriUE {stroke [] 0 setdash vpt 1.12 mul add M + hpt neg vpt -1.62 mul V + hpt 2 mul 0 V + hpt neg vpt 1.62 mul V closepath stroke} def +/TriDE {stroke [] 0 setdash vpt 1.12 mul sub M + hpt neg vpt 1.62 mul V + hpt 2 mul 0 V + hpt neg vpt -1.62 mul V closepath stroke} def +/PentE {stroke [] 0 setdash gsave + translate 0 hpt M 4 {72 rotate 0 hpt L} repeat + closepath stroke grestore} def +/CircE {stroke [] 0 setdash + hpt 0 360 arc stroke} def +/Opaque {gsave closepath 1 setgray fill grestore 0 setgray closepath} def +/DiaW {stroke [] 0 setdash vpt add M + hpt neg vpt neg V hpt vpt neg V + hpt vpt V hpt neg vpt V Opaque stroke} def +/BoxW {stroke [] 0 setdash exch hpt sub exch vpt add M + 0 vpt2 neg V hpt2 0 V 0 vpt2 V + hpt2 neg 0 V Opaque stroke} def +/TriUW {stroke [] 0 setdash vpt 1.12 mul add M + hpt neg vpt -1.62 mul V + hpt 2 mul 0 V + hpt neg vpt 1.62 mul V Opaque stroke} def +/TriDW {stroke [] 0 setdash vpt 1.12 mul sub M + hpt neg vpt 1.62 mul V + hpt 2 mul 0 V + hpt neg vpt -1.62 mul V Opaque stroke} def +/PentW {stroke [] 0 setdash gsave + translate 0 hpt M 4 {72 rotate 0 hpt L} repeat + Opaque stroke grestore} def +/CircW {stroke [] 0 setdash + hpt 0 360 arc Opaque stroke} def +/BoxFill {gsave Rec 1 setgray fill grestore} def +/Density { + /Fillden exch def + currentrgbcolor + /ColB exch def /ColG exch def /ColR exch def + /ColR ColR Fillden mul Fillden sub 1 add def + /ColG ColG Fillden mul Fillden sub 1 add def + /ColB ColB Fillden mul Fillden sub 1 add def + ColR ColG ColB setrgbcolor} def +/BoxColFill {gsave Rec PolyFill} def +/PolyFill {gsave Density fill grestore grestore} def +/h {rlineto rlineto rlineto gsave closepath fill grestore} bind def +% +% PostScript Level 1 Pattern Fill routine for rectangles +% Usage: x y w h s a XX PatternFill +% x,y = lower left corner of box to be filled +% w,h = width and height of box +% a = angle in degrees between lines and x-axis +% XX = 0/1 for no/yes cross-hatch +% +/PatternFill {gsave /PFa [ 9 2 roll ] def + PFa 0 get PFa 2 get 2 div add PFa 1 get PFa 3 get 2 div add translate + PFa 2 get -2 div PFa 3 get -2 div PFa 2 get PFa 3 get Rec + gsave 1 setgray fill grestore clip + currentlinewidth 0.5 mul setlinewidth + /PFs PFa 2 get dup mul PFa 3 get dup mul add sqrt def + 0 0 M PFa 5 get rotate PFs -2 div dup translate + 0 1 PFs PFa 4 get div 1 add floor cvi + {PFa 4 get mul 0 M 0 PFs V} for + 0 PFa 6 get ne { + 0 1 PFs PFa 4 get div 1 add floor cvi + {PFa 4 get mul 0 2 1 roll M PFs 0 V} for + } if + stroke grestore} def +% +/languagelevel where + {pop languagelevel} {1} ifelse + 2 lt + {/InterpretLevel1 true def} + {/InterpretLevel1 Level1 def} + ifelse +% +% PostScript level 2 pattern fill definitions +% +/Level2PatternFill { +/Tile8x8 {/PaintType 2 /PatternType 1 /TilingType 1 /BBox [0 0 8 8] /XStep 8 /YStep 8} + bind def +/KeepColor {currentrgbcolor [/Pattern /DeviceRGB] setcolorspace} bind def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 0 M 8 8 L 0 8 M 8 0 L stroke} +>> matrix makepattern +/Pat1 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 0 M 8 8 L 0 8 M 8 0 L stroke + 0 4 M 4 8 L 8 4 L 4 0 L 0 4 L stroke} +>> matrix makepattern +/Pat2 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 0 M 0 8 L + 8 8 L 8 0 L 0 0 L fill} +>> matrix makepattern +/Pat3 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -4 8 M 8 -4 L + 0 12 M 12 0 L stroke} +>> matrix makepattern +/Pat4 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -4 0 M 8 12 L + 0 -4 M 12 8 L stroke} +>> matrix makepattern +/Pat5 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -2 8 M 4 -4 L + 0 12 M 8 -4 L 4 12 M 10 0 L stroke} +>> matrix makepattern +/Pat6 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -2 0 M 4 12 L + 0 -4 M 8 12 L 4 -4 M 10 8 L stroke} +>> matrix makepattern +/Pat7 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 8 -2 M -4 4 L + 12 0 M -4 8 L 12 4 M 0 10 L stroke} +>> matrix makepattern +/Pat8 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 -2 M 12 4 L + -4 0 M 12 8 L -4 4 M 8 10 L stroke} +>> matrix makepattern +/Pat9 exch def +/Pattern1 {PatternBgnd KeepColor Pat1 setpattern} bind def +/Pattern2 {PatternBgnd KeepColor Pat2 setpattern} bind def +/Pattern3 {PatternBgnd KeepColor Pat3 setpattern} bind def +/Pattern4 {PatternBgnd KeepColor Landscape {Pat5} {Pat4} ifelse setpattern} bind def +/Pattern5 {PatternBgnd KeepColor Landscape {Pat4} {Pat5} ifelse setpattern} bind def +/Pattern6 {PatternBgnd KeepColor Landscape {Pat9} {Pat6} ifelse setpattern} bind def +/Pattern7 {PatternBgnd KeepColor Landscape {Pat8} {Pat7} ifelse setpattern} bind def +} def +% +% +%End of PostScript Level 2 code +% +/PatternBgnd { + TransparentPatterns {} {gsave 1 setgray fill grestore} ifelse +} def +% +% Substitute for Level 2 pattern fill codes with +% grayscale if Level 2 support is not selected. +% +/Level1PatternFill { +/Pattern1 {0.250 Density} bind def +/Pattern2 {0.500 Density} bind def +/Pattern3 {0.750 Density} bind def +/Pattern4 {0.125 Density} bind def +/Pattern5 {0.375 Density} bind def +/Pattern6 {0.625 Density} bind def +/Pattern7 {0.875 Density} bind def +} def +% +% Now test for support of Level 2 code +% +Level1 {Level1PatternFill} {Level2PatternFill} ifelse +% +/Symbol-Oblique /Symbol findfont [1 0 .167 1 0 0] makefont +dup length dict begin {1 index /FID eq {pop pop} {def} ifelse} forall +currentdict end definefont pop +/MFshow { + { dup 5 get 3 ge + { 5 get 3 eq {gsave} {grestore} ifelse } + {dup dup 0 get findfont exch 1 get scalefont setfont + [ currentpoint ] exch dup 2 get 0 exch R dup 5 get 2 ne {dup dup 6 + get exch 4 get {Gshow} {stringwidth pop 0 R} ifelse }if dup 5 get 0 eq + {dup 3 get {2 get neg 0 exch R pop} {pop aload pop M} ifelse} {dup 5 + get 1 eq {dup 2 get exch dup 3 get exch 6 get stringwidth pop -2 div + dup 0 R} {dup 6 get stringwidth pop -2 div 0 R 6 get + show 2 index {aload pop M neg 3 -1 roll neg R pop pop} {pop pop pop + pop aload pop M} ifelse }ifelse }ifelse } + ifelse } + forall} def +/Gswidth {dup type /stringtype eq {stringwidth} {pop (n) stringwidth} ifelse} def +/MFwidth {0 exch { dup 5 get 3 ge { 5 get 3 eq { 0 } { pop } ifelse } + {dup 3 get{dup dup 0 get findfont exch 1 get scalefont setfont + 6 get Gswidth pop add} {pop} ifelse} ifelse} forall} def +/MLshow { currentpoint stroke M + 0 exch R + Blacktext {gsave 0 setgray MFshow grestore} {MFshow} ifelse } bind def +/MRshow { currentpoint stroke M + exch dup MFwidth neg 3 -1 roll R + Blacktext {gsave 0 setgray MFshow grestore} {MFshow} ifelse } bind def +/MCshow { currentpoint stroke M + exch dup MFwidth -2 div 3 -1 roll R + Blacktext {gsave 0 setgray MFshow grestore} {MFshow} ifelse } bind def +/XYsave { [( ) 1 2 true false 3 ()] } bind def +/XYrestore { [( ) 1 2 true false 4 ()] } bind def +end +%%EndProlog +gnudict begin +gsave +doclip +50 50 translate +0.050 0.050 scale +0 setgray +newpath +(Helvetica) findfont 280 scalefont setfont +1.000 UL +LTb +1540 896 M +63 0 V +5176 0 R +-63 0 V +stroke +1372 896 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 0)] +] -93.3 MRshow +1.000 UL +LTb +1540 1372 M +63 0 V +5176 0 R +-63 0 V +stroke +1372 1372 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 50)] +] -93.3 MRshow +1.000 UL +LTb +1540 1848 M +63 0 V +5176 0 R +-63 0 V +stroke +1372 1848 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 100)] +] -93.3 MRshow +1.000 UL +LTb +1540 2324 M +63 0 V +5176 0 R +-63 0 V +stroke +1372 2324 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 150)] +] -93.3 MRshow +1.000 UL +LTb +1540 2800 M +63 0 V +5176 0 R +-63 0 V +stroke +1372 2800 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 200)] +] -93.3 MRshow +1.000 UL +LTb +1540 3275 M +63 0 V +5176 0 R +-63 0 V +stroke +1372 3275 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 250)] +] -93.3 MRshow +1.000 UL +LTb +1540 3751 M +63 0 V +5176 0 R +-63 0 V +stroke +1372 3751 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 300)] +] -93.3 MRshow +1.000 UL +LTb +1540 4227 M +63 0 V +5176 0 R +-63 0 V +stroke +1372 4227 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 350)] +] -93.3 MRshow +1.000 UL +LTb +1540 4703 M +63 0 V +5176 0 R +-63 0 V +stroke +1372 4703 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 400)] +] -93.3 MRshow +1.000 UL +LTb +2216 896 M +0 63 V +0 3744 R +0 -63 V +stroke +2216 616 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 0.05)] +] -93.3 MCshow +1.000 UL +LTb +3061 896 M +0 63 V +0 3744 R +0 -63 V +stroke +3061 616 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 0.1)] +] -93.3 MCshow +1.000 UL +LTb +3906 896 M +0 63 V +0 3744 R +0 -63 V +stroke +3906 616 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 0.15)] +] -93.3 MCshow +1.000 UL +LTb +4751 896 M +0 63 V +0 3744 R +0 -63 V +stroke +4751 616 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 0.2)] +] -93.3 MCshow +1.000 UL +LTb +5596 896 M +0 63 V +0 3744 R +0 -63 V +stroke +5596 616 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 0.25)] +] -93.3 MCshow +1.000 UL +LTb +6441 896 M +0 63 V +0 3744 R +0 -63 V +stroke +6441 616 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 0.3)] +] -93.3 MCshow +1.000 UL +LTb +1.000 UL +LTb +1540 4703 N +0 -3807 V +5239 0 V +0 3807 V +-5239 0 V +Z stroke +LCb setrgbcolor +392 2799 M +currentpoint gsave translate -270 rotate 0 0 moveto +[ [(Helvetica) 280.0 0.0 true true 0 (Frequency of Sense Confusion)] +] -93.3 MCshow +grestore +LTb +LCb setrgbcolor +4159 196 M +[ [(Helvetica) 280.0 0.0 true true 0 (Ontonote Sense Similarity)] +] -93.3 MCshow +LTb +2.000 UP +1.000 UL +LTb +% Begin plot #1 +2.000 UP +1.000 UL +LT0 +LCb setrgbcolor +5477 4500 M +[ [(Helvetica) 280.0 0.0 true true 0 (Actual \(avg\))] +] -93.3 MRshow +LT0 +5645 4500 M +798 0 V +1540 2300 M +169 -700 V +338 2008 V +2385 2324 L +338 228 V +338 -952 V +338 -142 V +338 -172 V +338 -238 V +338 505 V +338 -429 V +5089 896 L +338 0 V +338 0 V +338 0 V +338 0 V +338 0 V +1709 1600 Pls +2047 3608 Pls +2385 2324 Pls +2723 2552 Pls +3061 1600 Pls +3399 1458 Pls +3737 1286 Pls +4075 1048 Pls +4413 1553 Pls +4751 1124 Pls +5089 896 Pls +5427 896 Pls +5765 896 Pls +6103 896 Pls +6441 896 Pls +6779 896 Pls +6044 4500 Pls +% End plot #1 +% Begin plot #2 +2.000 UP +1.000 UL +LT1 +LC1 setrgbcolor +LCb setrgbcolor +5477 4220 M +[ [(Helvetica) 280.0 0.0 true true 0 (Baseline \(avg\))] +] -93.3 MRshow +LT1 +LC1 setrgbcolor +5645 4220 M +798 0 V +1540 2343 M +169 -534 V +338 2527 V +338 -906 V +2723 2342 L +3061 1195 L +338 -159 V +338 55 V +338 -78 V +338 47 V +338 -98 V +338 -66 V +338 0 V +338 0 V +338 0 V +338 0 V +338 0 V +1709 1809 Crs +2047 4336 Crs +2385 3430 Crs +2723 2342 Crs +3061 1195 Crs +3399 1036 Crs +3737 1091 Crs +4075 1013 Crs +4413 1060 Crs +4751 962 Crs +5089 896 Crs +5427 896 Crs +5765 896 Crs +6103 896 Crs +6441 896 Crs +6779 896 Crs +6044 4220 Crs +% End plot #2 +% Begin plot #3 +2.000 UP +1.000 UL +LT0 +LC2 setrgbcolor +LCb setrgbcolor +5477 3940 M +[ [(Helvetica) 280.0 0.0 true true 0 (Actual \(max\))] +] -93.3 MRshow +LT0 +LC2 setrgbcolor +5645 3940 M +798 0 V +1540 1876 M +1709 896 L +338 2027 V +338 828 V +2723 2228 L +338 -618 V +338 9 V +3737 896 L +338 152 V +338 895 V +4751 972 L +338 -76 V +338 0 V +338 0 V +338 0 V +338 257 V +6779 896 L +1709 896 Star +2047 2923 Star +2385 3751 Star +2723 2228 Star +3061 1610 Star +3399 1619 Star +3737 896 Star +4075 1048 Star +4413 1943 Star +4751 972 Star +5089 896 Star +5427 896 Star +5765 896 Star +6103 896 Star +6441 1153 Star +6779 896 Star +6044 3940 Star +% End plot #3 +% Begin plot #4 +2.000 UP +1.000 UL +LT3 +LCb setrgbcolor +5477 3660 M +[ [(Helvetica) 280.0 0.0 true true 0 (Baseline \(max\))] +] -93.3 MRshow +LT3 +5645 3660 M +798 0 V +1540 1801 M +1709 896 L +338 3382 V +338 22 V +2723 2073 L +338 -553 V +338 -430 V +3737 896 L +338 144 V +338 215 V +4751 911 L +338 -7 V +338 -8 V +338 0 V +338 0 V +338 128 V +6779 896 L +1709 896 Box +2047 4278 Box +2385 4300 Box +2723 2073 Box +3061 1520 Box +3399 1090 Box +3737 896 Box +4075 1040 Box +4413 1255 Box +4751 911 Box +5089 904 Box +5427 896 Box +5765 896 Box +6103 896 Box +6441 1024 Box +6779 896 Box +6044 3660 Box +% End plot #4 +1.000 UL +LTb +1540 4703 N +0 -3807 V +5239 0 V +0 3807 V +-5239 0 V +Z stroke +2.000 UP +1.000 UL +LTb +stroke +grestore +end +showpage +%%Trailer +%%DocumentFonts: Helvetica diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-gs-kmeans-test.key.max.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-gs-kmeans-test.key.max.actual new file mode 100644 index 00000000..614c4b43 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-gs-kmeans-test.key.max.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 206.0 +0.02 0.0 +0.04 213.0 +0.06 300.0 +0.08 140.0 +0.1 75.0 +0.12 76.0 +0.14 0.0 +0.16 16.0 +0.18 110.0 +0.2 8.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 27.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 16.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-gs-kmeans-test.key.max.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-gs-kmeans-test.key.max.baseline new file mode 100644 index 00000000..34cea07e --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-gs-kmeans-test.key.max.baseline @@ -0,0 +1,51 @@ +# similarity error_count +0.0 190.2333333333346 +0.02 0.0 +0.04 355.3333333333334 +0.06 357.65000000000003 +0.08 123.70000000000002 +0.1 65.55000000000001 +0.12 20.416666666666664 +0.14 0.0 +0.16 15.133333333333331 +0.18 37.75 +0.2 1.5999999999999999 +0.22 0.8 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 13.5 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 5.333333333333332 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-sc06-test.key.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-sc06-test.key.actual new file mode 100644 index 00000000..1146eeb3 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-sc06-test.key.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 188.0 +0.02 66.0 +0.04 267.0 +0.06 151.0 +0.08 137.0 +0.1 62.0 +0.12 42.0 +0.14 36.0 +0.16 16.0 +0.18 52.0 +0.2 24.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-sc06-test.key.avg.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-sc06-test.key.avg.actual new file mode 100644 index 00000000..1146eeb3 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-sc06-test.key.avg.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 188.0 +0.02 66.0 +0.04 267.0 +0.06 151.0 +0.08 137.0 +0.1 62.0 +0.12 42.0 +0.14 36.0 +0.16 16.0 +0.18 52.0 +0.2 24.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-sc06-test.key.avg.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-sc06-test.key.avg.baseline new file mode 100644 index 00000000..c0ab20ea --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-sc06-test.key.avg.baseline @@ -0,0 +1,51 @@ +# similarity error_count +0.0 183.38333333333443 +0.02 83.08333333333334 +0.04 320.66666666666663 +0.06 218.2833333333333 +0.08 141.56666666666666 +0.1 26.5 +0.12 19.0 +0.14 18.0 +0.16 10.333333333333332 +0.18 13.25 +0.2 6.933333333333332 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-sc06-test.key.baselines b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-sc06-test.key.baselines new file mode 100644 index 00000000..ee77c3b2 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-sc06-test.key.baselines @@ -0,0 +1,21 @@ +# similarity prob-of-confusion +0.0 0.21483375959079282 +0.02 0.09462915601023023 +0.04 0.3554987212276207 +0.06 0.2097186700767261 +0.08 0.06393861892583122 +0.1 0.01790281329923274 +0.12 0.01534526854219949 +0.14 0.0025575447570332483 +0.16 0.0076726342710997444 +0.18 0.0076726342710997444 +0.2 0.005115089514066497 +0.22 0.0025575447570332483 +0.24 0.0 +0.26 0.0 +0.28 0.0025575447570332483 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 diff --git 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setdash 2 copy exch vpt sub exch vpt sub vpt2 vpt Rec fill Bsquare} bind def +/S13 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt2 vpt Rec fill + 2 copy vpt Square fill Bsquare} bind def +/S14 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt2 vpt Rec fill + 2 copy exch vpt sub exch vpt Square fill Bsquare} bind def +/S15 {BL [] 0 setdash 2 copy Bsquare fill Bsquare} bind def +/D0 {gsave translate 45 rotate 0 0 S0 stroke grestore} bind def +/D1 {gsave translate 45 rotate 0 0 S1 stroke grestore} bind def +/D2 {gsave translate 45 rotate 0 0 S2 stroke grestore} bind def +/D3 {gsave translate 45 rotate 0 0 S3 stroke grestore} bind def +/D4 {gsave translate 45 rotate 0 0 S4 stroke grestore} bind def +/D5 {gsave translate 45 rotate 0 0 S5 stroke grestore} bind def +/D6 {gsave translate 45 rotate 0 0 S6 stroke grestore} bind def +/D7 {gsave translate 45 rotate 0 0 S7 stroke grestore} bind def +/D8 {gsave translate 45 rotate 0 0 S8 stroke grestore} bind def +/D9 {gsave translate 45 rotate 0 0 S9 stroke grestore} bind def +/D10 {gsave translate 45 rotate 0 0 S10 stroke grestore} bind def +/D11 {gsave translate 45 rotate 0 0 S11 stroke grestore} bind def +/D12 {gsave translate 45 rotate 0 0 S12 stroke grestore} bind def +/D13 {gsave translate 45 rotate 0 0 S13 stroke grestore} bind def +/D14 {gsave translate 45 rotate 0 0 S14 stroke grestore} bind def +/D15 {gsave translate 45 rotate 0 0 S15 stroke grestore} bind def +/DiaE {stroke [] 0 setdash vpt add M + hpt neg vpt neg V hpt vpt neg V + hpt vpt V hpt neg vpt V closepath stroke} def +/BoxE {stroke [] 0 setdash exch hpt sub exch vpt add M + 0 vpt2 neg V hpt2 0 V 0 vpt2 V + hpt2 neg 0 V closepath stroke} def +/TriUE {stroke [] 0 setdash vpt 1.12 mul add M + hpt neg vpt -1.62 mul V + hpt 2 mul 0 V + hpt neg vpt 1.62 mul V closepath stroke} def +/TriDE {stroke [] 0 setdash vpt 1.12 mul sub M + hpt neg vpt 1.62 mul V + hpt 2 mul 0 V + hpt neg vpt -1.62 mul V closepath stroke} def +/PentE {stroke [] 0 setdash gsave + 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/ColB exch def /ColG exch def /ColR exch def + /ColR ColR Fillden mul Fillden sub 1 add def + /ColG ColG Fillden mul Fillden sub 1 add def + /ColB ColB Fillden mul Fillden sub 1 add def + ColR ColG ColB setrgbcolor} def +/BoxColFill {gsave Rec PolyFill} def +/PolyFill {gsave Density fill grestore grestore} def +/h {rlineto rlineto rlineto gsave closepath fill grestore} bind def +% +% PostScript Level 1 Pattern Fill routine for rectangles +% Usage: x y w h s a XX PatternFill +% x,y = lower left corner of box to be filled +% w,h = width and height of box +% a = angle in degrees between lines and x-axis +% XX = 0/1 for no/yes cross-hatch +% +/PatternFill {gsave /PFa [ 9 2 roll ] def + PFa 0 get PFa 2 get 2 div add PFa 1 get PFa 3 get 2 div add translate + PFa 2 get -2 div PFa 3 get -2 div PFa 2 get PFa 3 get Rec + gsave 1 setgray fill grestore clip + currentlinewidth 0.5 mul setlinewidth + /PFs PFa 2 get dup mul PFa 3 get dup mul add sqrt def + 0 0 M PFa 5 get rotate PFs -2 div dup translate + 0 1 PFs PFa 4 get div 1 add floor cvi + {PFa 4 get mul 0 M 0 PFs V} for + 0 PFa 6 get ne { + 0 1 PFs PFa 4 get div 1 add floor cvi + {PFa 4 get mul 0 2 1 roll M PFs 0 V} for + } if + stroke grestore} def +% +/languagelevel where + {pop languagelevel} {1} ifelse + 2 lt + {/InterpretLevel1 true def} + {/InterpretLevel1 Level1 def} + ifelse +% +% PostScript level 2 pattern fill definitions +% +/Level2PatternFill { +/Tile8x8 {/PaintType 2 /PatternType 1 /TilingType 1 /BBox [0 0 8 8] /XStep 8 /YStep 8} + bind def +/KeepColor {currentrgbcolor [/Pattern /DeviceRGB] setcolorspace} bind def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 0 M 8 8 L 0 8 M 8 0 L stroke} +>> matrix makepattern +/Pat1 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 0 M 8 8 L 0 8 M 8 0 L stroke + 0 4 M 4 8 L 8 4 L 4 0 L 0 4 L stroke} +>> matrix makepattern +/Pat2 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 0 M 0 8 L + 8 8 L 8 0 L 0 0 L fill} +>> matrix makepattern +/Pat3 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -4 8 M 8 -4 L + 0 12 M 12 0 L stroke} +>> matrix makepattern +/Pat4 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -4 0 M 8 12 L + 0 -4 M 12 8 L stroke} +>> matrix makepattern +/Pat5 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -2 8 M 4 -4 L + 0 12 M 8 -4 L 4 12 M 10 0 L stroke} +>> matrix makepattern +/Pat6 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -2 0 M 4 12 L + 0 -4 M 8 12 L 4 -4 M 10 8 L stroke} +>> matrix makepattern +/Pat7 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 8 -2 M -4 4 L + 12 0 M -4 8 L 12 4 M 0 10 L stroke} +>> matrix makepattern +/Pat8 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 -2 M 12 4 L + -4 0 M 12 8 L -4 4 M 8 10 L stroke} +>> matrix makepattern +/Pat9 exch def +/Pattern1 {PatternBgnd KeepColor Pat1 setpattern} bind def +/Pattern2 {PatternBgnd KeepColor Pat2 setpattern} bind def +/Pattern3 {PatternBgnd KeepColor Pat3 setpattern} bind def +/Pattern4 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00000000..8869caf3 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-sc06-test.key.max.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 178.0 +0.02 0.0 +0.04 204.0 +0.06 286.0 +0.08 114.0 +0.1 63.0 +0.12 43.0 +0.14 0.0 +0.16 16.0 +0.18 88.0 +0.2 8.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 25.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 16.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-sc06-test.key.max.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-sc06-test.key.max.baseline new file mode 100644 index 00000000..c6371b0a --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-sc06-test.key.max.baseline @@ -0,0 +1,51 @@ +# similarity error_count +0.0 170.38333333333443 +0.02 0.0 +0.04 310.6500000000001 +0.06 299.70000000000005 +0.08 112.41666666666667 +0.1 54.900000000000006 +0.12 28.333333333333332 +0.14 0.0 +0.16 13.133333333333333 +0.18 31.25 +0.2 1.5999999999999999 +0.22 0.8 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 12.5 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 5.333333333333332 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-stkm-test.key.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-stkm-test.key.actual new file mode 100644 index 00000000..0f2c488f --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-stkm-test.key.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 211.0 +0.02 60.0 +0.04 269.0 +0.06 144.0 +0.08 173.0 +0.1 74.0 +0.12 59.0 +0.14 41.0 +0.16 16.0 +0.18 66.0 +0.2 24.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-stkm-test.key.avg.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-stkm-test.key.avg.actual new file mode 100644 index 00000000..0f2c488f --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-stkm-test.key.avg.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 211.0 +0.02 60.0 +0.04 269.0 +0.06 144.0 +0.08 173.0 +0.1 74.0 +0.12 59.0 +0.14 41.0 +0.16 16.0 +0.18 66.0 +0.2 24.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-stkm-test.key.avg.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-stkm-test.key.avg.baseline new file mode 100644 index 00000000..3088930b --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-stkm-test.key.avg.baseline @@ -0,0 +1,51 @@ +# similarity error_count +0.0 192.4666666666677 +0.02 100.33333333333331 +0.04 338.8333333333334 +0.06 256.31666666666666 +0.08 148.38333333333335 +0.1 31.450000000000003 +0.12 14.75 +0.14 20.5 +0.16 10.333333333333332 +0.18 16.5 +0.2 7.133333333333332 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-stkm-test.key.baselines b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-stkm-test.key.baselines new file mode 100644 index 00000000..ee77c3b2 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-stkm-test.key.baselines @@ -0,0 +1,21 @@ +# similarity prob-of-confusion +0.0 0.21483375959079282 +0.02 0.09462915601023023 +0.04 0.3554987212276207 +0.06 0.2097186700767261 +0.08 0.06393861892583122 +0.1 0.01790281329923274 +0.12 0.01534526854219949 +0.14 0.0025575447570332483 +0.16 0.0076726342710997444 +0.18 0.0076726342710997444 +0.2 0.005115089514066497 +0.22 0.0025575447570332483 +0.24 0.0 +0.26 0.0 +0.28 0.0025575447570332483 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-stkm-test.key.eps 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{pop 1} if 10 mul /udl exch def} def +/PL {stroke userlinewidth setlinewidth + Rounded {1 setlinejoin 1 setlinecap} if} def +% Default Line colors +/LCw {1 1 1} def +/LCb {0 0 0} def +/LCa {0 0 0} def +/LC0 {1 0 0} def +/LC1 {0 1 0} def +/LC2 {0 0 1} def +/LC3 {1 0 1} def +/LC4 {0 1 1} def +/LC5 {1 1 0} def +/LC6 {0 0 0} def +/LC7 {1 0.3 0} def +/LC8 {0.5 0.5 0.5} def +% Default Line Types +/LTw {PL [] 1 setgray} def +/LTb {BL [] LCb DL} def +/LTa {AL [1 udl mul 2 udl mul] 0 setdash LCa setrgbcolor} def +/LT0 {PL [] LC0 DL} def +/LT1 {PL [4 dl1 2 dl2] LC1 DL} def +/LT2 {PL [2 dl1 3 dl2] LC2 DL} def +/LT3 {PL [1 dl1 1.5 dl2] LC3 DL} def +/LT4 {PL [6 dl1 2 dl2 1 dl1 2 dl2] LC4 DL} def +/LT5 {PL [3 dl1 3 dl2 1 dl1 3 dl2] LC5 DL} def +/LT6 {PL [2 dl1 2 dl2 2 dl1 6 dl2] LC6 DL} def +/LT7 {PL [1 dl1 2 dl2 6 dl1 2 dl2 1 dl1 2 dl2] LC7 DL} def +/LT8 {PL [2 dl1 2 dl2 2 dl1 2 dl2 2 dl1 2 dl2 2 dl1 4 dl2] LC8 DL} def +/Pnt {stroke [] 0 setdash gsave 1 setlinecap M 0 0 V stroke grestore} def +/Dia {stroke [] 0 setdash 2 copy vpt add M + hpt neg vpt neg V hpt vpt neg V + hpt vpt V hpt neg vpt V closepath stroke + Pnt} def +/Pls {stroke [] 0 setdash vpt sub M 0 vpt2 V + currentpoint stroke M + hpt neg vpt neg R hpt2 0 V stroke + } def +/Box {stroke [] 0 setdash 2 copy exch hpt sub exch vpt add M + 0 vpt2 neg V hpt2 0 V 0 vpt2 V + hpt2 neg 0 V closepath stroke + Pnt} def +/Crs {stroke [] 0 setdash exch hpt sub exch vpt add M + hpt2 vpt2 neg V currentpoint stroke M + hpt2 neg 0 R hpt2 vpt2 V stroke} def +/TriU {stroke [] 0 setdash 2 copy vpt 1.12 mul add M + hpt neg vpt -1.62 mul V + hpt 2 mul 0 V + hpt neg vpt 1.62 mul V closepath stroke + Pnt} def +/Star {2 copy Pls Crs} def +/BoxF {stroke [] 0 setdash exch hpt sub exch vpt add M + 0 vpt2 neg V hpt2 0 V 0 vpt2 V + hpt2 neg 0 V closepath fill} def +/TriUF {stroke [] 0 setdash vpt 1.12 mul add M + hpt neg vpt -1.62 mul V + hpt 2 mul 0 V + hpt neg vpt 1.62 mul V closepath fill} def +/TriD {stroke [] 0 setdash 2 copy vpt 1.12 mul sub M + hpt neg vpt 1.62 mul V + hpt 2 mul 0 V + hpt neg vpt -1.62 mul V closepath stroke + Pnt} def +/TriDF {stroke [] 0 setdash vpt 1.12 mul sub M + hpt neg vpt 1.62 mul V + hpt 2 mul 0 V + hpt neg vpt -1.62 mul V closepath fill} def +/DiaF {stroke [] 0 setdash vpt add M + hpt neg vpt neg V hpt vpt neg V + hpt vpt V hpt neg vpt V closepath fill} def +/Pent {stroke [] 0 setdash 2 copy gsave + translate 0 hpt M 4 {72 rotate 0 hpt L} repeat + closepath stroke grestore Pnt} def +/PentF {stroke [] 0 setdash gsave + translate 0 hpt M 4 {72 rotate 0 hpt L} repeat + closepath fill grestore} def +/Circle {stroke [] 0 setdash 2 copy + hpt 0 360 arc stroke Pnt} def +/CircleF {stroke [] 0 setdash hpt 0 360 arc fill} def +/C0 {BL [] 0 setdash 2 copy moveto vpt 90 450 arc} bind def +/C1 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 0 90 arc closepath fill + vpt 0 360 arc closepath} bind def +/C2 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 90 180 arc closepath fill + vpt 0 360 arc closepath} bind def +/C3 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 0 180 arc closepath fill + vpt 0 360 arc closepath} bind def +/C4 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 180 270 arc closepath fill + vpt 0 360 arc closepath} bind def +/C5 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 0 90 arc + 2 copy moveto + 2 copy vpt 180 270 arc closepath fill + vpt 0 360 arc} bind def +/C6 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 90 270 arc closepath fill + vpt 0 360 arc closepath} bind def +/C7 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 0 270 arc closepath fill + vpt 0 360 arc closepath} bind def +/C8 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 270 360 arc closepath fill + vpt 0 360 arc closepath} bind def +/C9 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 270 450 arc closepath fill + vpt 0 360 arc closepath} bind def +/C10 {BL [] 0 setdash 2 copy 2 copy moveto vpt 270 360 arc closepath fill + 2 copy moveto + 2 copy vpt 90 180 arc closepath fill + vpt 0 360 arc closepath} bind def +/C11 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 0 180 arc closepath fill + 2 copy moveto + 2 copy vpt 270 360 arc closepath fill + vpt 0 360 arc closepath} bind def +/C12 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 180 360 arc closepath fill + vpt 0 360 arc closepath} bind def +/C13 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 0 90 arc closepath fill + 2 copy moveto + 2 copy vpt 180 360 arc closepath fill + vpt 0 360 arc closepath} bind def +/C14 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 90 360 arc closepath fill + vpt 0 360 arc} bind def +/C15 {BL [] 0 setdash 2 copy vpt 0 360 arc closepath fill + vpt 0 360 arc closepath} bind def +/Rec {newpath 4 2 roll moveto 1 index 0 rlineto 0 exch rlineto + neg 0 rlineto closepath} bind def +/Square {dup Rec} bind def +/Bsquare {vpt sub exch vpt sub exch vpt2 Square} bind def +/S0 {BL [] 0 setdash 2 copy moveto 0 vpt rlineto BL Bsquare} bind def +/S1 {BL [] 0 setdash 2 copy vpt Square fill Bsquare} bind def +/S2 {BL [] 0 setdash 2 copy exch vpt sub exch vpt Square fill Bsquare} bind def +/S3 {BL [] 0 setdash 2 copy exch vpt sub exch vpt2 vpt Rec fill Bsquare} bind def +/S4 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt Square fill Bsquare} bind def +/S5 {BL [] 0 setdash 2 copy 2 copy vpt Square fill + exch vpt sub exch vpt sub vpt Square fill Bsquare} bind def +/S6 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt vpt2 Rec fill Bsquare} bind def +/S7 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt vpt2 Rec fill + 2 copy vpt Square fill Bsquare} bind def +/S8 {BL [] 0 setdash 2 copy vpt sub vpt Square fill Bsquare} bind def +/S9 {BL [] 0 setdash 2 copy vpt sub vpt vpt2 Rec fill Bsquare} bind def +/S10 {BL [] 0 setdash 2 copy vpt sub vpt Square fill 2 copy exch vpt sub exch vpt Square fill + Bsquare} bind def +/S11 {BL [] 0 setdash 2 copy vpt sub vpt Square fill 2 copy exch vpt sub exch vpt2 vpt Rec fill + Bsquare} bind def +/S12 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt2 vpt Rec fill Bsquare} bind def +/S13 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt2 vpt Rec fill + 2 copy vpt Square fill Bsquare} bind def +/S14 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt2 vpt Rec fill + 2 copy exch vpt sub exch vpt Square fill Bsquare} bind def +/S15 {BL [] 0 setdash 2 copy Bsquare fill Bsquare} bind def +/D0 {gsave translate 45 rotate 0 0 S0 stroke grestore} bind def +/D1 {gsave translate 45 rotate 0 0 S1 stroke grestore} bind def +/D2 {gsave translate 45 rotate 0 0 S2 stroke grestore} bind def +/D3 {gsave translate 45 rotate 0 0 S3 stroke grestore} bind def +/D4 {gsave translate 45 rotate 0 0 S4 stroke grestore} bind def +/D5 {gsave translate 45 rotate 0 0 S5 stroke grestore} bind def +/D6 {gsave translate 45 rotate 0 0 S6 stroke grestore} bind def +/D7 {gsave translate 45 rotate 0 0 S7 stroke grestore} bind def +/D8 {gsave translate 45 rotate 0 0 S8 stroke grestore} bind def +/D9 {gsave translate 45 rotate 0 0 S9 stroke grestore} bind def +/D10 {gsave translate 45 rotate 0 0 S10 stroke grestore} bind def +/D11 {gsave translate 45 rotate 0 0 S11 stroke grestore} bind def +/D12 {gsave translate 45 rotate 0 0 S12 stroke grestore} bind def +/D13 {gsave translate 45 rotate 0 0 S13 stroke grestore} bind def +/D14 {gsave translate 45 rotate 0 0 S14 stroke grestore} bind def +/D15 {gsave translate 45 rotate 0 0 S15 stroke grestore} bind def +/DiaE {stroke [] 0 setdash vpt add M + hpt neg vpt neg V hpt vpt neg V + hpt vpt V hpt neg vpt V closepath stroke} def +/BoxE {stroke [] 0 setdash exch hpt sub exch vpt add M + 0 vpt2 neg V hpt2 0 V 0 vpt2 V + hpt2 neg 0 V closepath stroke} def +/TriUE {stroke [] 0 setdash vpt 1.12 mul add M + hpt neg vpt -1.62 mul V + hpt 2 mul 0 V + hpt neg vpt 1.62 mul V closepath stroke} def +/TriDE {stroke [] 0 setdash vpt 1.12 mul sub M + hpt neg vpt 1.62 mul V + hpt 2 mul 0 V + hpt neg vpt -1.62 mul V closepath stroke} def +/PentE {stroke [] 0 setdash gsave + translate 0 hpt M 4 {72 rotate 0 hpt L} repeat + closepath stroke grestore} def +/CircE {stroke [] 0 setdash + hpt 0 360 arc stroke} def +/Opaque {gsave closepath 1 setgray fill grestore 0 setgray closepath} def +/DiaW {stroke [] 0 setdash vpt add M + hpt neg vpt neg V hpt vpt neg V + hpt vpt V hpt neg vpt V Opaque stroke} def +/BoxW {stroke [] 0 setdash exch hpt sub exch vpt add M + 0 vpt2 neg V hpt2 0 V 0 vpt2 V + hpt2 neg 0 V Opaque stroke} def +/TriUW {stroke [] 0 setdash vpt 1.12 mul add M + hpt neg vpt -1.62 mul V + hpt 2 mul 0 V + hpt neg vpt 1.62 mul V Opaque stroke} def +/TriDW {stroke [] 0 setdash vpt 1.12 mul sub M + hpt neg vpt 1.62 mul V + hpt 2 mul 0 V + hpt neg vpt -1.62 mul V Opaque stroke} def +/PentW {stroke [] 0 setdash gsave + translate 0 hpt M 4 {72 rotate 0 hpt L} repeat + Opaque stroke grestore} def +/CircW {stroke [] 0 setdash + hpt 0 360 arc Opaque stroke} def +/BoxFill {gsave Rec 1 setgray fill grestore} def +/Density { + /Fillden exch def + currentrgbcolor + /ColB exch def /ColG exch def /ColR exch def + /ColR ColR Fillden mul Fillden sub 1 add def + /ColG ColG Fillden mul Fillden sub 1 add def + /ColB ColB Fillden mul Fillden sub 1 add def + ColR ColG ColB setrgbcolor} def +/BoxColFill {gsave Rec PolyFill} def +/PolyFill {gsave Density fill grestore grestore} def +/h {rlineto rlineto rlineto gsave closepath fill grestore} bind def +% +% PostScript Level 1 Pattern Fill routine for rectangles +% Usage: x y w h s a XX PatternFill +% x,y = lower left corner of box to be filled +% w,h = width and height of box +% a = angle in degrees between lines and x-axis +% XX = 0/1 for no/yes cross-hatch +% +/PatternFill {gsave /PFa [ 9 2 roll ] def + PFa 0 get PFa 2 get 2 div add PFa 1 get PFa 3 get 2 div add translate + PFa 2 get -2 div PFa 3 get -2 div PFa 2 get PFa 3 get Rec + gsave 1 setgray fill grestore clip + currentlinewidth 0.5 mul setlinewidth + /PFs PFa 2 get dup mul PFa 3 get dup mul add sqrt def + 0 0 M PFa 5 get rotate PFs -2 div dup translate + 0 1 PFs PFa 4 get div 1 add floor cvi + {PFa 4 get mul 0 M 0 PFs V} for + 0 PFa 6 get ne { + 0 1 PFs PFa 4 get div 1 add floor cvi + {PFa 4 get mul 0 2 1 roll M PFs 0 V} for + } if + stroke grestore} def +% +/languagelevel where + {pop languagelevel} {1} ifelse + 2 lt + {/InterpretLevel1 true def} + {/InterpretLevel1 Level1 def} + ifelse +% +% PostScript level 2 pattern fill definitions +% +/Level2PatternFill { +/Tile8x8 {/PaintType 2 /PatternType 1 /TilingType 1 /BBox [0 0 8 8] /XStep 8 /YStep 8} + bind def +/KeepColor {currentrgbcolor [/Pattern /DeviceRGB] setcolorspace} bind def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 0 M 8 8 L 0 8 M 8 0 L stroke} +>> matrix makepattern +/Pat1 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 0 M 8 8 L 0 8 M 8 0 L stroke + 0 4 M 4 8 L 8 4 L 4 0 L 0 4 L stroke} +>> matrix makepattern +/Pat2 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 0 M 0 8 L + 8 8 L 8 0 L 0 0 L fill} +>> matrix makepattern +/Pat3 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -4 8 M 8 -4 L + 0 12 M 12 0 L stroke} +>> matrix makepattern +/Pat4 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -4 0 M 8 12 L + 0 -4 M 12 8 L stroke} +>> matrix makepattern +/Pat5 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -2 8 M 4 -4 L + 0 12 M 8 -4 L 4 12 M 10 0 L stroke} +>> matrix makepattern +/Pat6 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -2 0 M 4 12 L + 0 -4 M 8 12 L 4 -4 M 10 8 L stroke} +>> matrix makepattern +/Pat7 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 8 -2 M -4 4 L + 12 0 M -4 8 L 12 4 M 0 10 L stroke} +>> matrix makepattern +/Pat8 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 -2 M 12 4 L + -4 0 M 12 8 L -4 4 M 8 10 L stroke} +>> matrix makepattern +/Pat9 exch def +/Pattern1 {PatternBgnd KeepColor Pat1 setpattern} bind def +/Pattern2 {PatternBgnd KeepColor Pat2 setpattern} bind def +/Pattern3 {PatternBgnd KeepColor Pat3 setpattern} bind def +/Pattern4 {PatternBgnd KeepColor Landscape {Pat5} {Pat4} ifelse setpattern} bind def +/Pattern5 {PatternBgnd KeepColor Landscape {Pat4} {Pat5} ifelse setpattern} bind def +/Pattern6 {PatternBgnd KeepColor Landscape {Pat9} {Pat6} ifelse setpattern} bind def +/Pattern7 {PatternBgnd KeepColor Landscape {Pat8} {Pat7} ifelse setpattern} bind def +} def +% +% +%End of PostScript Level 2 code +% +/PatternBgnd { + TransparentPatterns {} {gsave 1 setgray fill grestore} ifelse +} def +% +% Substitute for Level 2 pattern fill codes with +% grayscale if Level 2 support is not selected. +% +/Level1PatternFill { +/Pattern1 {0.250 Density} bind def +/Pattern2 {0.500 Density} bind def +/Pattern3 {0.750 Density} bind def +/Pattern4 {0.125 Density} bind def +/Pattern5 {0.375 Density} bind def +/Pattern6 {0.625 Density} bind def +/Pattern7 {0.875 Density} bind def +} def +% +% Now test for support of Level 2 code +% +Level1 {Level1PatternFill} {Level2PatternFill} ifelse +% +/Symbol-Oblique /Symbol findfont [1 0 .167 1 0 0] makefont +dup length dict begin {1 index /FID eq {pop pop} {def} ifelse} forall +currentdict end definefont pop +/MFshow { + { dup 5 get 3 ge + { 5 get 3 eq {gsave} {grestore} ifelse } + {dup dup 0 get findfont exch 1 get scalefont setfont + [ currentpoint ] exch dup 2 get 0 exch R dup 5 get 2 ne {dup dup 6 + get exch 4 get {Gshow} {stringwidth pop 0 R} ifelse }if dup 5 get 0 eq + {dup 3 get {2 get neg 0 exch R pop} {pop aload pop M} ifelse} {dup 5 + get 1 eq {dup 2 get exch dup 3 get exch 6 get stringwidth pop -2 div + dup 0 R} {dup 6 get stringwidth pop -2 div 0 R 6 get + show 2 index {aload pop M neg 3 -1 roll neg R pop pop} {pop pop pop + pop aload pop M} ifelse }ifelse }ifelse } + ifelse } + forall} def +/Gswidth {dup type /stringtype eq {stringwidth} {pop (n) stringwidth} ifelse} def +/MFwidth {0 exch { dup 5 get 3 ge { 5 get 3 eq { 0 } { pop } ifelse } + {dup 3 get{dup dup 0 get findfont exch 1 get scalefont setfont + 6 get Gswidth pop add} {pop} ifelse} ifelse} forall} def +/MLshow { currentpoint stroke M + 0 exch R + Blacktext {gsave 0 setgray MFshow grestore} {MFshow} ifelse } bind def +/MRshow { currentpoint stroke M + exch dup MFwidth neg 3 -1 roll R + Blacktext {gsave 0 setgray MFshow grestore} {MFshow} ifelse } bind def +/MCshow { currentpoint stroke M + exch dup MFwidth -2 div 3 -1 roll R + Blacktext {gsave 0 setgray MFshow grestore} {MFshow} ifelse } bind def +/XYsave { [( ) 1 2 true false 3 ()] } bind def +/XYrestore { [( ) 1 2 true false 4 ()] } bind def +end +%%EndProlog +gnudict begin +gsave +doclip +50 50 translate +0.050 0.050 scale +0 setgray +newpath +(Helvetica) findfont 280 scalefont setfont +1.000 UL +LTb +1540 896 M +63 0 V +5176 0 R +-63 0 V +stroke +1372 896 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 0)] +] -93.3 MRshow +1.000 UL +LTb +1540 1440 M +63 0 V +5176 0 R +-63 0 V +stroke +1372 1440 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 50)] +] -93.3 MRshow +1.000 UL +LTb +1540 1984 M +63 0 V +5176 0 R +-63 0 V +stroke +1372 1984 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 100)] +] -93.3 MRshow +1.000 UL +LTb +1540 2528 M +63 0 V +5176 0 R +-63 0 V +stroke +1372 2528 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 150)] +] -93.3 MRshow +1.000 UL +LTb +1540 3071 M +63 0 V +5176 0 R +-63 0 V +stroke +1372 3071 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 200)] +] -93.3 MRshow +1.000 UL +LTb +1540 3615 M +63 0 V +5176 0 R +-63 0 V +stroke +1372 3615 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 250)] +] -93.3 MRshow +1.000 UL +LTb +1540 4159 M +63 0 V +5176 0 R +-63 0 V +stroke +1372 4159 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 300)] +] -93.3 MRshow +1.000 UL +LTb +1540 4703 M +63 0 V +5176 0 R +-63 0 V +stroke +1372 4703 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 350)] +] -93.3 MRshow +1.000 UL +LTb +2216 896 M +0 63 V +0 3744 R +0 -63 V +stroke +2216 616 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 0.05)] +] -93.3 MCshow +1.000 UL +LTb +3061 896 M +0 63 V +0 3744 R +0 -63 V +stroke +3061 616 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 0.1)] +] -93.3 MCshow +1.000 UL +LTb +3906 896 M +0 63 V +0 3744 R +0 -63 V +stroke +3906 616 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 0.15)] +] -93.3 MCshow +1.000 UL +LTb +4751 896 M +0 63 V +0 3744 R +0 -63 V +stroke +4751 616 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 0.2)] +] -93.3 MCshow +1.000 UL +LTb +5596 896 M +0 63 V +0 3744 R +0 -63 V +stroke +5596 616 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 0.25)] +] -93.3 MCshow +1.000 UL +LTb +6441 896 M +0 63 V +0 3744 R +0 -63 V +stroke +6441 616 M +[ [(Helvetica) 280.0 0.0 true true 0 ( 0.3)] +] -93.3 MCshow +1.000 UL +LTb +1.000 UL +LTb +1540 4703 N +0 -3807 V +5239 0 V +0 3807 V +-5239 0 V +Z stroke +LCb setrgbcolor +392 2799 M +currentpoint gsave translate -270 rotate 0 0 moveto +[ [(Helvetica) 280.0 0.0 true true 0 (Frequency of Sense Confusion)] +] -93.3 MCshow +grestore +LTb +LCb setrgbcolor +4159 196 M +[ [(Helvetica) 280.0 0.0 true true 0 (Ontonote Sense Similarity)] +] -93.3 MCshow +LTb +2.000 UP +1.000 UL +LTb +% Begin plot #1 +2.000 UP +1.000 UL +LT0 +LCb setrgbcolor +5477 4500 M +[ [(Helvetica) 280.0 0.0 true true 0 (Actual \(avg\))] +] -93.3 MRshow +LT0 +5645 4500 M +798 0 V +1540 2370 M +169 -821 V +338 2273 V +2385 2462 L +338 316 V +3061 1701 L +338 -163 V +338 -196 V +338 -272 V +338 544 V +338 -457 V +5089 896 L +338 0 V +338 0 V +338 0 V +338 0 V +338 0 V +1709 1549 Pls +2047 3822 Pls +2385 2462 Pls +2723 2778 Pls +3061 1701 Pls +3399 1538 Pls +3737 1342 Pls +4075 1070 Pls +4413 1614 Pls +4751 1157 Pls +5089 896 Pls +5427 896 Pls +5765 896 Pls +6103 896 Pls +6441 896 Pls +6779 896 Pls +6044 4500 Pls +% End plot #1 +% Begin plot #2 +2.000 UP +1.000 UL +LT1 +LC1 setrgbcolor +LCb setrgbcolor +5477 4220 M +[ [(Helvetica) 280.0 0.0 true true 0 (Baseline \(avg\))] +] -93.3 MRshow +LT1 +LC1 setrgbcolor +5645 4220 M +798 0 V +1540 2488 M +169 -501 V +338 2595 V +338 -898 V +2723 2510 L +3061 1238 L +338 -182 V +338 63 V +338 -111 V +338 67 V +4751 974 L +338 -78 V +338 0 V +338 0 V +338 0 V +338 0 V +338 0 V +1709 1987 Crs +2047 4582 Crs +2385 3684 Crs +2723 2510 Crs +3061 1238 Crs +3399 1056 Crs +3737 1119 Crs +4075 1008 Crs +4413 1075 Crs +4751 974 Crs +5089 896 Crs +5427 896 Crs +5765 896 Crs +6103 896 Crs +6441 896 Crs +6779 896 Crs +6044 4220 Crs +% End plot #2 +% Begin plot #3 +2.000 UP +1.000 UL +LT0 +LC2 setrgbcolor +LCb setrgbcolor +5477 3940 M +[ [(Helvetica) 280.0 0.0 true true 0 (Actual \(max\))] +] -93.3 MRshow +LT0 +LC2 setrgbcolor +5645 3940 M +798 0 V +1540 1973 M +1709 896 L +338 2034 V +338 1088 V +2723 2430 L +338 -718 V +338 0 V +3737 896 L +338 174 V +338 990 V +4751 983 L +338 -87 V +338 0 V +338 0 V +338 0 V +338 294 V +6779 896 L +1709 896 Star +2047 2930 Star +2385 4018 Star +2723 2430 Star +3061 1712 Star +3399 1712 Star +3737 896 Star +4075 1070 Star +4413 2060 Star +4751 983 Star +5089 896 Star +5427 896 Star +5765 896 Star +6103 896 Star +6441 1190 Star +6779 896 Star +6044 3940 Star +% End plot #3 +% Begin plot #4 +2.000 UP +1.000 UL +LT3 +LCb setrgbcolor +5477 3660 M +[ [(Helvetica) 280.0 0.0 true true 0 (Baseline \(max\))] +] -93.3 MRshow +LT3 +5645 3660 M +798 0 V +1540 1858 M +1709 896 L +338 3700 V +338 53 V +2723 2179 L +338 -581 V +338 -476 V +3737 896 L +338 143 V +338 259 V +4751 916 L +338 -11 V +338 -9 V +338 0 V +338 0 V +338 147 V +6779 896 L +1709 896 Box +2047 4596 Box +2385 4649 Box +2723 2179 Box +3061 1598 Box +3399 1122 Box +3737 896 Box +4075 1039 Box +4413 1298 Box +4751 916 Box +5089 905 Box +5427 896 Box +5765 896 Box +6103 896 Box +6441 1043 Box +6779 896 Box +6044 3660 Box +% End plot #4 +1.000 UL +LTb +1540 4703 N +0 -3807 V +5239 0 V +0 3807 V +-5239 0 V +Z stroke +2.000 UP +1.000 UL +LTb +stroke +grestore +end +showpage +%%Trailer +%%DocumentFonts: Helvetica diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-stkm-test.key.max.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-stkm-test.key.max.actual new file mode 100644 index 00000000..951f5337 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-stkm-test.key.max.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 198.0 +0.02 0.0 +0.04 187.0 +0.06 287.0 +0.08 141.0 +0.1 75.0 +0.12 75.0 +0.14 0.0 +0.16 16.0 +0.18 107.0 +0.2 8.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 27.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 16.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-stkm-test.key.max.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-stkm-test.key.max.baseline new file mode 100644 index 00000000..6e6f67a7 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-pos-stkm-test.key.max.baseline @@ -0,0 +1,51 @@ +# similarity error_count +0.0 176.9666666666677 +0.02 0.0 +0.04 340.1833333333333 +0.06 345.00000000000006 +0.08 117.98333333333333 +0.1 64.55000000000001 +0.12 20.75 +0.14 0.0 +0.16 13.133333333333333 +0.18 37.0 +0.2 1.7999999999999998 +0.22 0.8 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 13.5 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 5.333333333333332 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-rel-stkm-test.key.eps b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-rel-stkm-test.key.eps new file mode 100644 index 00000000..e69de29b diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-sc06-test.key.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-sc06-test.key.actual new file mode 100644 index 00000000..35d08b5e --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-sc06-test.key.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 195.0 +0.02 62.0 +0.04 246.0 +0.06 141.0 +0.08 148.0 +0.1 72.0 +0.12 52.0 +0.14 32.0 +0.16 16.0 +0.18 53.0 +0.2 21.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-sc06-test.key.avg.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-sc06-test.key.avg.actual new file mode 100644 index 00000000..35d08b5e --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-sc06-test.key.avg.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 195.0 +0.02 62.0 +0.04 246.0 +0.06 141.0 +0.08 148.0 +0.1 72.0 +0.12 52.0 +0.14 32.0 +0.16 16.0 +0.18 53.0 +0.2 21.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-sc06-test.key.avg.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-sc06-test.key.avg.baseline new file mode 100644 index 00000000..73b1a839 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-sc06-test.key.avg.baseline @@ -0,0 +1,51 @@ +# similarity error_count +0.0 174.63333333333424 +0.02 83.33333333333333 +0.04 332.66666666666663 +0.06 225.2 +0.08 126.43333333333334 +0.1 29.4 +0.12 16.25 +0.14 19.5 +0.16 10.333333333333332 +0.18 13.25 +0.2 6.999999999999999 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-sc06-test.key.baselines b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-sc06-test.key.baselines new file mode 100644 index 00000000..ee77c3b2 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-sc06-test.key.baselines @@ -0,0 +1,21 @@ +# similarity prob-of-confusion +0.0 0.21483375959079282 +0.02 0.09462915601023023 +0.04 0.3554987212276207 +0.06 0.2097186700767261 +0.08 0.06393861892583122 +0.1 0.01790281329923274 +0.12 0.01534526854219949 +0.14 0.0025575447570332483 +0.16 0.0076726342710997444 +0.18 0.0076726342710997444 +0.2 0.005115089514066497 +0.22 0.0025575447570332483 +0.24 0.0 +0.26 0.0 +0.28 0.0025575447570332483 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-sc06-test.key.eps 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+LT1 +LC3 setrgbcolor +5645 3660 M +798 0 V +1540 1767 M +1709 896 L +338 3477 V +338 -91 V +2723 2056 L +338 -581 V +338 -359 V +3737 896 L +338 141 V +338 215 V +4751 918 L +338 -15 V +338 -7 V +338 0 V +338 0 V +338 147 V +6779 896 L +1709 896 Box +2047 4373 Box +2385 4282 Box +2723 2056 Box +3061 1475 Box +3399 1116 Box +3737 896 Box +4075 1037 Box +4413 1252 Box +4751 918 Box +5089 903 Box +5427 896 Box +5765 896 Box +6103 896 Box +6441 1043 Box +6779 896 Box +6044 3660 Box +% End plot #4 +1.000 UL +LTb +1540 4703 N +0 -3807 V +5239 0 V +0 3807 V +-5239 0 V +Z stroke +2.000 UP +1.000 UL +LTb +stroke +grestore +end +showpage +%%Trailer +%%DocumentFonts: Helvetica diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-sc06-test.key.max.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-sc06-test.key.max.actual new file mode 100644 index 00000000..10dc0b02 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-sc06-test.key.max.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 183.0 +0.02 0.0 +0.04 178.0 +0.06 271.0 +0.08 127.0 +0.1 69.0 +0.12 61.0 +0.14 0.0 +0.16 16.0 +0.18 85.0 +0.2 6.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 27.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 15.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-sc06-test.key.max.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-sc06-test.key.max.baseline new file mode 100644 index 00000000..89e23fea --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-sc06-test.key.max.baseline @@ -0,0 +1,51 @@ +# similarity error_count +0.0 160.13333333333424 +0.02 0.0 +0.04 319.6333333333333 +0.06 311.31666666666655 +0.08 106.68333333333334 +0.1 53.2 +0.12 20.25 +0.14 0.0 +0.16 12.933333333333332 +0.18 32.75 +0.2 1.9999999999999998 +0.22 0.6000000000000001 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 13.5 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 4.999999999999999 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-stkm-test.key.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-stkm-test.key.actual new file mode 100644 index 00000000..6bf27075 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-stkm-test.key.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 206.0 +0.02 68.0 +0.04 262.0 +0.06 136.0 +0.08 172.0 +0.1 74.0 +0.12 59.0 +0.14 40.0 +0.16 17.0 +0.18 66.0 +0.2 23.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-stkm-test.key.avg.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-stkm-test.key.avg.actual new file mode 100644 index 00000000..6bf27075 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-stkm-test.key.avg.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 206.0 +0.02 68.0 +0.04 262.0 +0.06 136.0 +0.08 172.0 +0.1 74.0 +0.12 59.0 +0.14 40.0 +0.16 17.0 +0.18 66.0 +0.2 23.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-stkm-test.key.avg.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-stkm-test.key.avg.baseline new file mode 100644 index 00000000..ee4c7e9a --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-stkm-test.key.avg.baseline @@ -0,0 +1,51 @@ +# similarity error_count +0.0 191.2666666666678 +0.02 92.58333333333333 +0.04 342.05000000000007 +0.06 251.6 +0.08 146.63333333333335 +0.1 31.450000000000003 +0.12 14.75 +0.14 20.5 +0.16 8.333333333333332 +0.18 16.5 +0.2 7.333333333333332 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-stkm-test.key.baselines b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-stkm-test.key.baselines new file mode 100644 index 00000000..ee77c3b2 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-stkm-test.key.baselines @@ -0,0 +1,21 @@ +# similarity prob-of-confusion +0.0 0.21483375959079282 +0.02 0.09462915601023023 +0.04 0.3554987212276207 +0.06 0.2097186700767261 +0.08 0.06393861892583122 +0.1 0.01790281329923274 +0.12 0.01534526854219949 +0.14 0.0025575447570332483 +0.16 0.0076726342710997444 +0.18 0.0076726342710997444 +0.2 0.005115089514066497 +0.22 0.0025575447570332483 +0.24 0.0 +0.26 0.0 +0.28 0.0025575447570332483 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-stkm-test.key.eps b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-stkm-test.key.eps new file mode 100644 index 00000000..e81fc6f6 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-stkm-test.key.eps @@ -0,0 +1,841 @@ +%!PS-Adobe-2.0 EPSF-2.0 +%%Title: 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+0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 16.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-stkm-test.key.max.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-stkm-test.key.max.baseline new file mode 100644 index 00000000..912e7966 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-stkm-test.key.max.baseline @@ -0,0 +1,51 @@ +# similarity error_count +0.0 174.7666666666678 +0.02 0.0 +0.04 333.6666666666667 +0.06 343.26666666666665 +0.08 117.43333333333334 +0.1 64.35000000000001 +0.12 19.75 +0.14 0.0 +0.16 11.133333333333333 +0.18 37.0 +0.2 1.9999999999999998 +0.22 0.8 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 13.5 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 5.333333333333332 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-stkm-test.key.png b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-stkm-test.key.png new file mode 100644 index 00000000..e5f16034 Binary files /dev/null and b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wc-wordsi-stkm-test.key.png differ diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-cbc-test.key.avg.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-cbc-test.key.avg.actual new file mode 100644 index 00000000..9422986f --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-cbc-test.key.avg.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 169.0 +0.02 53.0 +0.04 246.0 +0.06 136.0 +0.08 130.0 +0.1 60.0 +0.12 49.0 +0.14 33.0 +0.16 9.0 +0.18 41.0 +0.2 12.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-cbc-test.key.avg.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-cbc-test.key.avg.baseline new file mode 100644 index 00000000..0dadd720 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-cbc-test.key.avg.baseline @@ -0,0 +1,51 @@ +# similarity error_count +0.0 152.40000000000055 +0.02 87.08333333333333 +0.04 281.1500000000001 +0.06 198.25000000000003 +0.08 123.83333333333334 +0.1 30.550000000000004 +0.12 21.75 +0.14 17.5 +0.16 6.833333333333334 +0.18 10.25 +0.2 8.399999999999999 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-cbc-test.key.eps b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-cbc-test.key.eps new file mode 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0 S12 stroke grestore} bind def +/D13 {gsave translate 45 rotate 0 0 S13 stroke grestore} bind def +/D14 {gsave translate 45 rotate 0 0 S14 stroke grestore} bind def +/D15 {gsave translate 45 rotate 0 0 S15 stroke grestore} bind def +/DiaE {stroke [] 0 setdash vpt add M + hpt neg vpt neg V hpt vpt neg V + hpt vpt V hpt neg vpt V closepath stroke} def +/BoxE {stroke [] 0 setdash exch hpt sub exch vpt add M + 0 vpt2 neg V hpt2 0 V 0 vpt2 V + hpt2 neg 0 V closepath stroke} def +/TriUE {stroke [] 0 setdash vpt 1.12 mul add M + hpt neg vpt -1.62 mul V + hpt 2 mul 0 V + hpt neg vpt 1.62 mul V closepath stroke} def +/TriDE {stroke [] 0 setdash vpt 1.12 mul sub M + hpt neg vpt 1.62 mul V + hpt 2 mul 0 V + hpt neg vpt -1.62 mul V closepath stroke} def +/PentE {stroke [] 0 setdash gsave + translate 0 hpt M 4 {72 rotate 0 hpt L} repeat + closepath stroke grestore} def +/CircE {stroke [] 0 setdash + hpt 0 360 arc stroke} def +/Opaque {gsave closepath 1 setgray fill grestore 0 setgray closepath} def +/DiaW {stroke [] 0 setdash vpt add M + hpt neg vpt neg V hpt vpt neg V + hpt vpt V hpt neg vpt V Opaque stroke} def +/BoxW {stroke [] 0 setdash exch hpt sub exch vpt add M + 0 vpt2 neg V hpt2 0 V 0 vpt2 V + hpt2 neg 0 V Opaque stroke} def +/TriUW {stroke [] 0 setdash vpt 1.12 mul add M + hpt neg vpt -1.62 mul V + hpt 2 mul 0 V + hpt neg vpt 1.62 mul V Opaque stroke} def +/TriDW {stroke [] 0 setdash vpt 1.12 mul sub M + hpt neg vpt 1.62 mul V + hpt 2 mul 0 V + hpt neg vpt -1.62 mul V Opaque stroke} def +/PentW {stroke [] 0 setdash gsave + translate 0 hpt M 4 {72 rotate 0 hpt L} repeat + Opaque stroke grestore} def +/CircW {stroke [] 0 setdash + hpt 0 360 arc Opaque stroke} def +/BoxFill {gsave Rec 1 setgray fill grestore} def +/Density { + /Fillden exch def + currentrgbcolor + /ColB exch def /ColG exch def /ColR exch def + /ColR ColR Fillden mul Fillden sub 1 add def + /ColG ColG Fillden mul Fillden sub 1 add def + /ColB ColB Fillden mul Fillden sub 1 add def + ColR ColG ColB 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grestore} def +% +/languagelevel where + {pop languagelevel} {1} ifelse + 2 lt + {/InterpretLevel1 true def} + {/InterpretLevel1 Level1 def} + ifelse +% +% PostScript level 2 pattern fill definitions +% +/Level2PatternFill { +/Tile8x8 {/PaintType 2 /PatternType 1 /TilingType 1 /BBox [0 0 8 8] /XStep 8 /YStep 8} + bind def +/KeepColor {currentrgbcolor [/Pattern /DeviceRGB] setcolorspace} bind def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 0 M 8 8 L 0 8 M 8 0 L stroke} +>> matrix makepattern +/Pat1 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 0 M 8 8 L 0 8 M 8 0 L stroke + 0 4 M 4 8 L 8 4 L 4 0 L 0 4 L stroke} +>> matrix makepattern +/Pat2 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 0 M 0 8 L + 8 8 L 8 0 L 0 0 L fill} +>> matrix makepattern +/Pat3 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -4 8 M 8 -4 L + 0 12 M 12 0 L stroke} +>> matrix makepattern +/Pat4 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -4 0 M 8 12 L + 0 -4 M 12 8 L stroke} +>> matrix makepattern +/Pat5 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -2 8 M 4 -4 L + 0 12 M 8 -4 L 4 12 M 10 0 L stroke} +>> matrix makepattern +/Pat6 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -2 0 M 4 12 L + 0 -4 M 8 12 L 4 -4 M 10 8 L stroke} +>> matrix makepattern +/Pat7 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 8 -2 M -4 4 L + 12 0 M -4 8 L 12 4 M 0 10 L stroke} +>> matrix makepattern +/Pat8 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 -2 M 12 4 L + -4 0 M 12 8 L -4 4 M 8 10 L stroke} +>> matrix makepattern +/Pat9 exch def +/Pattern1 {PatternBgnd KeepColor Pat1 setpattern} bind def +/Pattern2 {PatternBgnd KeepColor Pat2 setpattern} bind def +/Pattern3 {PatternBgnd KeepColor Pat3 setpattern} bind def +/Pattern4 {PatternBgnd KeepColor Landscape {Pat5} {Pat4} ifelse setpattern} bind def +/Pattern5 {PatternBgnd KeepColor Landscape {Pat4} {Pat5} ifelse setpattern} bind def +/Pattern6 {PatternBgnd KeepColor Landscape 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+2047 4304 Box +2385 4567 Box +2723 2255 Box +3061 1465 Box +3399 1252 Box +3737 896 Box +4075 1016 Box +4413 1248 Box +4751 914 Box +5089 904 Box +5427 896 Box +5765 896 Box +6103 896 Box +6441 1061 Box +6779 896 Box +6044 3660 Box +% End plot #4 +1.000 UL +LTb +1540 4703 N +0 -3807 V +5239 0 V +0 3807 V +-5239 0 V +Z stroke +2.000 UP +1.000 UL +LTb +stroke +grestore +end +showpage +%%Trailer +%%DocumentFonts: Helvetica diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-cbc-test.key.max.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-cbc-test.key.max.actual new file mode 100644 index 00000000..1f5c5c70 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-cbc-test.key.max.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 150.0 +0.02 0.0 +0.04 192.0 +0.06 249.0 +0.08 90.0 +0.1 76.0 +0.12 59.0 +0.14 0.0 +0.16 10.0 +0.18 74.0 +0.2 6.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 26.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 6.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-cbc-test.key.max.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-cbc-test.key.max.baseline new file mode 100644 index 00000000..10806a70 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-cbc-test.key.max.baseline @@ -0,0 +1,51 @@ +# similarity error_count +0.0 140.90000000000055 +0.02 0.0 +0.04 268.55000000000007 +0.06 289.31666666666666 +0.08 107.11666666666667 +0.1 44.85 +0.12 28.083333333333332 +0.14 0.0 +0.16 9.433333333333334 +0.18 27.75 +0.2 1.4 +0.22 0.6000000000000001 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 13.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 6.999999999999997 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-gs-kmeans-test.key.avg.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-gs-kmeans-test.key.avg.actual new file mode 100644 index 00000000..9456cafe --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-gs-kmeans-test.key.avg.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 221.0 +0.02 74.0 +0.04 285.0 +0.06 150.0 +0.08 174.0 +0.1 74.0 +0.12 59.0 +0.14 41.0 +0.16 16.0 +0.18 69.0 +0.2 24.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-gs-kmeans-test.key.avg.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-gs-kmeans-test.key.avg.baseline new file mode 100644 index 00000000..8996b7dc --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-gs-kmeans-test.key.avg.baseline @@ -0,0 +1,51 @@ +# similarity error_count +0.0 208.2333333333346 +0.02 95.91666666666666 +0.04 361.46666666666687 +0.06 266.19999999999993 +0.08 151.96666666666667 +0.1 31.450000000000003 +0.12 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+0.3 27.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 16.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-gs-kmeans-test.key.max.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-gs-kmeans-test.key.max.baseline new file mode 100644 index 00000000..34cea07e --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-gs-kmeans-test.key.max.baseline @@ -0,0 +1,51 @@ +# similarity error_count +0.0 190.2333333333346 +0.02 0.0 +0.04 355.3333333333334 +0.06 357.65000000000003 +0.08 123.70000000000002 +0.1 65.55000000000001 +0.12 20.416666666666664 +0.14 0.0 +0.16 15.133333333333331 +0.18 37.75 +0.2 1.5999999999999999 +0.22 0.8 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 13.5 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 5.333333333333332 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-sc06-test.key.avg.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-sc06-test.key.avg.actual new file mode 100644 index 00000000..bec3310d --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-sc06-test.key.avg.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 207.0 +0.02 66.0 +0.04 281.0 +0.06 149.0 +0.08 134.0 +0.1 70.0 +0.12 49.0 +0.14 25.0 +0.16 16.0 +0.18 40.0 +0.2 24.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-sc06-test.key.avg.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-sc06-test.key.avg.baseline new file mode 100644 index 00000000..e6cf4119 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-sc06-test.key.avg.baseline @@ -0,0 +1,51 @@ +# similarity error_count +0.0 197.88333333333446 +0.02 86.5 +0.04 335.8666666666668 +0.06 228.4333333333333 +0.08 115.8 +0.1 31.05 +0.12 16.0 +0.14 21.0 +0.16 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add M + hpt neg vpt -1.62 mul V + hpt 2 mul 0 V + hpt neg vpt 1.62 mul V Opaque stroke} def +/TriDW {stroke [] 0 setdash vpt 1.12 mul sub M + hpt neg vpt 1.62 mul V + hpt 2 mul 0 V + hpt neg vpt -1.62 mul V Opaque stroke} def +/PentW {stroke [] 0 setdash gsave + translate 0 hpt M 4 {72 rotate 0 hpt L} repeat + Opaque stroke grestore} def +/CircW {stroke [] 0 setdash + hpt 0 360 arc Opaque stroke} def +/BoxFill {gsave Rec 1 setgray fill grestore} def +/Density { + /Fillden exch def + currentrgbcolor + /ColB exch def /ColG exch def /ColR exch def + /ColR ColR Fillden mul Fillden sub 1 add def + /ColG ColG Fillden mul Fillden sub 1 add def + /ColB ColB Fillden mul Fillden sub 1 add def + ColR ColG ColB setrgbcolor} def +/BoxColFill {gsave Rec PolyFill} def +/PolyFill {gsave Density fill grestore grestore} def +/h {rlineto rlineto rlineto gsave closepath fill grestore} bind def +% +% PostScript Level 1 Pattern Fill routine for rectangles +% Usage: x y w h s a XX PatternFill +% x,y = lower left corner of box to be filled +% w,h = width and height of box +% a = angle in degrees between lines and x-axis +% XX = 0/1 for no/yes cross-hatch +% +/PatternFill {gsave /PFa [ 9 2 roll ] def + PFa 0 get PFa 2 get 2 div add PFa 1 get PFa 3 get 2 div add translate + PFa 2 get -2 div PFa 3 get -2 div PFa 2 get PFa 3 get Rec + gsave 1 setgray fill grestore clip + currentlinewidth 0.5 mul setlinewidth + /PFs PFa 2 get dup mul PFa 3 get dup mul add sqrt def + 0 0 M PFa 5 get rotate PFs -2 div dup translate + 0 1 PFs PFa 4 get div 1 add floor cvi + {PFa 4 get mul 0 M 0 PFs V} for + 0 PFa 6 get ne { + 0 1 PFs PFa 4 get div 1 add floor cvi + {PFa 4 get mul 0 2 1 roll M PFs 0 V} for + } if + stroke grestore} def +% +/languagelevel where + {pop languagelevel} {1} ifelse + 2 lt + {/InterpretLevel1 true def} + {/InterpretLevel1 Level1 def} + ifelse +% +% PostScript level 2 pattern fill definitions +% +/Level2PatternFill { +/Tile8x8 {/PaintType 2 /PatternType 1 /TilingType 1 /BBox [0 0 8 8] /XStep 8 /YStep 8} + bind def +/KeepColor {currentrgbcolor [/Pattern /DeviceRGB] setcolorspace} bind def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 0 M 8 8 L 0 8 M 8 0 L stroke} +>> matrix makepattern +/Pat1 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 0 M 8 8 L 0 8 M 8 0 L stroke + 0 4 M 4 8 L 8 4 L 4 0 L 0 4 L stroke} +>> matrix makepattern +/Pat2 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 0 M 0 8 L + 8 8 L 8 0 L 0 0 L fill} +>> matrix makepattern +/Pat3 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -4 8 M 8 -4 L + 0 12 M 12 0 L stroke} +>> matrix makepattern +/Pat4 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -4 0 M 8 12 L + 0 -4 M 12 8 L stroke} +>> matrix makepattern +/Pat5 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -2 8 M 4 -4 L + 0 12 M 8 -4 L 4 12 M 10 0 L stroke} +>> matrix makepattern +/Pat6 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -2 0 M 4 12 L + 0 -4 M 8 12 L 4 -4 M 10 8 L stroke} +>> matrix makepattern +/Pat7 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 8 -2 M -4 4 L + 12 0 M -4 8 L 12 4 M 0 10 L stroke} +>> matrix makepattern +/Pat8 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 -2 M 12 4 L + -4 0 M 12 8 L -4 4 M 8 10 L stroke} +>> matrix makepattern +/Pat9 exch def +/Pattern1 {PatternBgnd KeepColor Pat1 setpattern} bind def +/Pattern2 {PatternBgnd KeepColor Pat2 setpattern} bind def +/Pattern3 {PatternBgnd KeepColor Pat3 setpattern} bind def +/Pattern4 {PatternBgnd KeepColor Landscape {Pat5} {Pat4} ifelse setpattern} bind def +/Pattern5 {PatternBgnd KeepColor Landscape {Pat4} {Pat5} ifelse setpattern} bind def +/Pattern6 {PatternBgnd KeepColor Landscape {Pat9} {Pat6} ifelse setpattern} bind def +/Pattern7 {PatternBgnd KeepColor Landscape {Pat8} {Pat7} ifelse setpattern} bind def +} def +% +% +%End of PostScript Level 2 code +% +/PatternBgnd { + TransparentPatterns {} {gsave 1 setgray fill grestore} ifelse +} def +% +% Substitute for Level 2 pattern fill codes with +% grayscale if Level 2 support is not selected. +% +/Level1PatternFill { +/Pattern1 {0.250 Density} bind def +/Pattern2 {0.500 Density} bind def +/Pattern3 {0.750 Density} bind def +/Pattern4 {0.125 Density} bind def +/Pattern5 {0.375 Density} bind def +/Pattern6 {0.625 Density} bind def +/Pattern7 {0.875 Density} bind def +} def +% +% Now test for support of Level 2 code +% +Level1 {Level1PatternFill} {Level2PatternFill} ifelse +% +/Symbol-Oblique /Symbol findfont [1 0 .167 1 0 0] makefont +dup length dict begin {1 index /FID eq {pop pop} {def} ifelse} forall +currentdict end definefont pop +/MFshow { + { dup 5 get 3 ge + { 5 get 3 eq {gsave} {grestore} ifelse } + {dup dup 0 get findfont exch 1 get scalefont setfont + [ currentpoint ] exch dup 2 get 0 exch R dup 5 get 2 ne {dup dup 6 + get exch 4 get {Gshow} {stringwidth pop 0 R} ifelse }if dup 5 get 0 eq + {dup 3 get {2 get neg 0 exch R pop} {pop aload pop M} ifelse} {dup 5 + get 1 eq {dup 2 get exch dup 3 get exch 6 get stringwidth pop -2 div + dup 0 R} {dup 6 get stringwidth pop -2 div 0 R 6 get + show 2 index {aload pop M neg 3 -1 roll neg R pop pop} {pop pop pop + pop aload pop M} ifelse }ifelse }ifelse } + ifelse } + forall} def +/Gswidth {dup type /stringtype eq {stringwidth} {pop (n) stringwidth} ifelse} def +/MFwidth {0 exch { dup 5 get 3 ge { 5 get 3 eq { 0 } { pop } ifelse } + {dup 3 get{dup dup 0 get findfont exch 1 get scalefont setfont + 6 get Gswidth pop add} {pop} ifelse} ifelse} forall} def +/MLshow { currentpoint stroke M + 0 exch R + Blacktext {gsave 0 setgray MFshow grestore} {MFshow} ifelse } bind def +/MRshow { currentpoint stroke M + exch dup MFwidth neg 3 -1 roll R + Blacktext {gsave 0 setgray MFshow grestore} {MFshow} ifelse } bind def +/MCshow { currentpoint stroke M + exch dup MFwidth -2 div 3 -1 roll R + Blacktext {gsave 0 setgray MFshow grestore} {MFshow} ifelse } bind def +/XYsave { [( ) 1 2 true false 3 ()] } bind def +/XYrestore { [( ) 1 2 true false 4 ()] } bind def 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+5089 896 Pls +5427 896 Pls +5765 896 Pls +6103 896 Pls +6441 896 Pls +6779 896 Pls +6044 4500 Pls +% End plot #1 +% Begin plot #2 +2.000 UP +1.000 UL +LT1 +LC1 setrgbcolor +LCb setrgbcolor +5477 4220 M +[ [(Helvetica) 280.0 0.0 true true 0 (Baseline \(avg\))] +] -93.3 MRshow +LT1 +LC1 setrgbcolor +5645 4220 M +798 0 V +1540 2443 M +169 -606 V +338 2712 V +2385 3381 L +2723 2156 L +338 -922 V +338 -164 V +338 54 V +338 -105 V +338 -14 V +338 -31 V +338 -78 V +338 0 V +338 0 V +338 0 V +338 0 V +338 0 V +1709 1837 Crs +2047 4549 Crs +2385 3381 Crs +2723 2156 Crs +3061 1234 Crs +3399 1070 Crs +3737 1124 Crs +4075 1019 Crs +4413 1005 Crs +4751 974 Crs +5089 896 Crs +5427 896 Crs +5765 896 Crs +6103 896 Crs +6441 896 Crs +6779 896 Crs +6044 4220 Crs +% End plot #2 +% Begin plot #3 +2.000 UP +1.000 UL +LT0 +LC2 setrgbcolor +LCb setrgbcolor +5477 3940 M +[ [(Helvetica) 280.0 0.0 true true 0 (Actual \(max\))] +] -93.3 MRshow +LT0 +LC2 setrgbcolor +5645 3940 M +798 0 V +1540 1940 M +1709 896 L +338 2241 V +338 924 V +2723 2136 L +338 -392 V +338 -315 V +3737 896 L +338 174 V +338 533 V +4751 983 L +338 -87 V +338 0 V +338 0 V +338 0 V +338 283 V +6779 896 L +1709 896 Star +2047 3137 Star +2385 4061 Star +2723 2136 Star +3061 1744 Star +3399 1429 Star +3737 896 Star +4075 1070 Star +4413 1603 Star +4751 983 Star +5089 896 Star +5427 896 Star +5765 896 Star +6103 896 Star +6441 1179 Star +6779 896 Star +6044 3940 Star +% End plot #3 +% Begin plot #4 +2.000 UP +1.000 UL +LT3 +LCb setrgbcolor +5477 3660 M +[ [(Helvetica) 280.0 0.0 true true 0 (Baseline \(max\))] +] -93.3 MRshow +LT3 +5645 3660 M +798 0 V +1540 1874 M +1709 896 L +338 3616 V +338 -250 V +2723 2022 L +338 -669 V +338 -156 V +3737 896 L +338 154 V +338 183 V +4751 916 L +338 -11 V +338 -9 V +338 0 V +338 0 V +338 141 V +6779 896 L +1709 896 Box +2047 4512 Box +2385 4262 Box +2723 2022 Box +3061 1353 Box +3399 1197 Box +3737 896 Box +4075 1050 Box +4413 1233 Box +4751 916 Box +5089 905 Box +5427 896 Box +5765 896 Box +6103 896 Box +6441 1037 Box +6779 896 Box +6044 3660 Box +% End plot #4 +1.000 UL +LTb +1540 4703 N +0 -3807 V +5239 0 V +0 3807 V +-5239 0 V +Z stroke +2.000 UP +1.000 UL +LTb +stroke +grestore +end +showpage +%%Trailer +%%DocumentFonts: Helvetica diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-sc06-test.key.max.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-sc06-test.key.max.actual new file mode 100644 index 00000000..ed4ed364 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-sc06-test.key.max.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 192.0 +0.02 0.0 +0.04 206.0 +0.06 291.0 +0.08 114.0 +0.1 78.0 +0.12 49.0 +0.14 0.0 +0.16 16.0 +0.18 65.0 +0.2 8.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 26.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 16.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-sc06-test.key.max.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-sc06-test.key.max.baseline new file mode 100644 index 00000000..8904d2d9 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-sc06-test.key.max.baseline @@ -0,0 +1,51 @@ +# similarity error_count +0.0 179.88333333333446 +0.02 0.0 +0.04 332.4000000000001 +0.06 309.4166666666667 +0.08 103.51666666666665 +0.1 42.05 +0.12 27.66666666666667 +0.14 0.0 +0.16 14.133333333333333 +0.18 31.0 +0.2 1.7999999999999998 +0.22 0.8 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 13.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 5.333333333333332 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-stkm-test.key.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-stkm-test.key.actual new file mode 100644 index 00000000..d8c4be80 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-stkm-test.key.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 220.0 +0.02 74.0 +0.04 283.0 +0.06 150.0 +0.08 173.0 +0.1 74.0 +0.12 59.0 +0.14 41.0 +0.16 16.0 +0.18 69.0 +0.2 24.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-stkm-test.key.avg.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-stkm-test.key.avg.actual new file mode 100644 index 00000000..d8c4be80 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-stkm-test.key.avg.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 220.0 +0.02 74.0 +0.04 283.0 +0.06 150.0 +0.08 173.0 +0.1 74.0 +0.12 59.0 +0.14 41.0 +0.16 16.0 +0.18 69.0 +0.2 24.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-stkm-test.key.avg.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-stkm-test.key.avg.baseline new file mode 100644 index 00000000..b64eefb1 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-stkm-test.key.avg.baseline @@ -0,0 +1,51 @@ +# similarity error_count +0.0 206.9833333333346 +0.02 95.66666666666666 +0.04 360.71666666666687 +0.06 265.44999999999993 +0.08 151.46666666666667 +0.1 31.450000000000003 +0.12 14.75 +0.14 20.5 +0.16 11.833333333333332 +0.18 17.25 +0.2 6.933333333333332 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 0.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-stkm-test.key.baselines b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-stkm-test.key.baselines new file mode 100644 index 00000000..ee77c3b2 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-stkm-test.key.baselines @@ -0,0 +1,21 @@ +# similarity prob-of-confusion +0.0 0.21483375959079282 +0.02 0.09462915601023023 +0.04 0.3554987212276207 +0.06 0.2097186700767261 +0.08 0.06393861892583122 +0.1 0.01790281329923274 +0.12 0.01534526854219949 +0.14 0.0025575447570332483 +0.16 0.0076726342710997444 +0.18 0.0076726342710997444 +0.2 0.005115089514066497 +0.22 0.0025575447570332483 +0.24 0.0 +0.26 0.0 +0.28 0.0025575447570332483 +0.3 0.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-stkm-test.key.eps b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-stkm-test.key.eps new file mode 100644 index 00000000..91301a62 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-stkm-test.key.eps @@ -0,0 +1,851 @@ +%!PS-Adobe-2.0 EPSF-2.0 +%%Title: semEval-2010-dv-wordsi-rel-stkm-test.key.eps +%%Creator: gnuplot 4.3 patchlevel 0 +%%CreationDate: Sun May 15 23:41:17 2011 +%%DocumentFonts: (atend) +%%BoundingBox: 50 50 410 302 +%%EndComments +%%BeginProlog +/gnudict 256 dict def +gnudict begin +% +% The following true/false flags may be edited by hand if desired. +% The unit line width and grayscale image gamma correction may also be changed. +% +/Color true def +/Blacktext false def +/Solid false def +/Dashlength 1 def +/Landscape false def +/Level1 false def 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0 V + hpt neg vpt -1.62 mul V closepath stroke} def +/PentE {stroke [] 0 setdash gsave + translate 0 hpt M 4 {72 rotate 0 hpt L} repeat + closepath stroke grestore} def +/CircE {stroke [] 0 setdash + hpt 0 360 arc stroke} def +/Opaque {gsave closepath 1 setgray fill grestore 0 setgray closepath} def +/DiaW {stroke [] 0 setdash vpt add M + hpt neg vpt neg V hpt vpt neg V + hpt vpt V hpt neg vpt V Opaque stroke} def +/BoxW {stroke [] 0 setdash exch hpt sub exch vpt add M + 0 vpt2 neg V hpt2 0 V 0 vpt2 V + hpt2 neg 0 V Opaque stroke} def +/TriUW {stroke [] 0 setdash vpt 1.12 mul add M + hpt neg vpt -1.62 mul V + hpt 2 mul 0 V + hpt neg vpt 1.62 mul V Opaque stroke} def +/TriDW {stroke [] 0 setdash vpt 1.12 mul sub M + hpt neg vpt 1.62 mul V + hpt 2 mul 0 V + hpt neg vpt -1.62 mul V Opaque stroke} def +/PentW {stroke [] 0 setdash gsave + translate 0 hpt M 4 {72 rotate 0 hpt L} repeat + Opaque stroke grestore} def +/CircW {stroke [] 0 setdash + hpt 0 360 arc Opaque stroke} def +/BoxFill {gsave Rec 1 setgray fill grestore} def +/Density { + /Fillden exch def + currentrgbcolor + /ColB exch def /ColG exch def /ColR exch def + /ColR ColR Fillden mul Fillden sub 1 add def + /ColG ColG Fillden mul Fillden sub 1 add def + /ColB ColB Fillden mul Fillden sub 1 add def + ColR ColG ColB setrgbcolor} def +/BoxColFill {gsave Rec PolyFill} def +/PolyFill {gsave Density fill grestore grestore} def +/h {rlineto rlineto rlineto gsave closepath fill grestore} bind def +% +% PostScript Level 1 Pattern Fill routine for rectangles +% Usage: x y w h s a XX PatternFill +% x,y = lower left corner of box to be filled +% w,h = width and height of box +% a = angle in degrees between lines and x-axis +% XX = 0/1 for no/yes cross-hatch +% +/PatternFill {gsave /PFa [ 9 2 roll ] def + PFa 0 get PFa 2 get 2 div add PFa 1 get PFa 3 get 2 div add translate + PFa 2 get -2 div PFa 3 get -2 div PFa 2 get PFa 3 get Rec + gsave 1 setgray fill grestore clip + currentlinewidth 0.5 mul setlinewidth + /PFs PFa 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+%%DocumentFonts: Helvetica diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-stkm-test.key.max.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-stkm-test.key.max.actual new file mode 100644 index 00000000..e118feb5 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-stkm-test.key.max.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 205.0 +0.02 0.0 +0.04 211.0 +0.06 300.0 +0.08 139.0 +0.1 75.0 +0.12 76.0 +0.14 0.0 +0.16 16.0 +0.18 110.0 +0.2 8.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 27.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 16.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-stkm-test.key.max.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-stkm-test.key.max.baseline new file mode 100644 index 00000000..0465d0b0 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-dv-wordsi-rel-stkm-test.key.max.baseline @@ -0,0 +1,51 @@ +# similarity error_count +0.0 188.9833333333346 +0.02 0.0 +0.04 354.3333333333334 +0.06 357.15000000000003 +0.08 122.95000000000002 +0.1 65.55000000000001 +0.12 20.416666666666664 +0.14 0.0 +0.16 14.633333333333333 +0.18 37.75 +0.2 1.5999999999999999 +0.22 0.8 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 13.5 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 5.333333333333332 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-fscore.avg.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-fscore.avg.actual new file mode 100644 index 00000000..a31cebe4 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-fscore.avg.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 229.0 +0.02 0.0 +0.04 239.0 +0.06 305.0 +0.08 143.0 +0.1 80.0 +0.12 61.0 +0.14 0.0 +0.16 17.0 +0.18 111.0 +0.2 8.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 28.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 16.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-fscore.avg.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-fscore.avg.baseline new file mode 100644 index 00000000..b190708f --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-fscore.avg.baseline @@ -0,0 +1,51 @@ +# similarity error_count +0.0 219.68333333333422 +0.02 0.0 +0.04 354.4500000000001 +0.06 365.95000000000005 +0.08 126.40000000000002 +0.1 67.4 +0.12 27.91666666666667 +0.14 0.0 +0.16 15.466666666666665 +0.18 38.0 +0.2 1.5999999999999999 +0.22 0.8 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 14.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 5.333333333333332 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-mfs.avg.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-mfs.avg.actual new file mode 100644 index 00000000..84a955a1 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-mfs.avg.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 232.0 +0.02 0.0 +0.04 239.0 +0.06 305.0 +0.08 143.0 +0.1 80.0 +0.12 61.0 +0.14 0.0 +0.16 17.0 +0.18 111.0 +0.2 8.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 28.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 16.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-mfs.avg.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-mfs.avg.baseline new file mode 100644 index 00000000..f3f57502 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-mfs.avg.baseline @@ -0,0 +1,51 @@ +# similarity error_count +0.0 224.01666666666748 +0.02 0.0 +0.04 353.11666666666673 +0.06 365.95000000000005 +0.08 126.40000000000002 +0.1 67.4 +0.12 27.91666666666667 +0.14 0.0 +0.16 15.466666666666665 +0.18 38.0 +0.2 1.5999999999999999 +0.22 0.8 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 14.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 5.333333333333332 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-sup.avg.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-sup.avg.actual new file mode 100644 index 00000000..0201b749 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-sup.avg.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 172.0 +0.02 0.0 +0.04 200.0 +0.06 285.0 +0.08 82.0 +0.1 80.0 +0.12 60.0 +0.14 0.0 +0.16 13.0 +0.18 61.0 +0.2 5.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 28.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 11.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-sup.avg.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-sup.avg.baseline new file mode 100644 index 00000000..93e97441 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-sup.avg.baseline @@ -0,0 +1,51 @@ +# similarity error_count +0.0 171.03333333333413 +0.02 0.0 +0.04 297.85 +0.06 309.56666666666666 +0.08 99.86666666666667 +0.1 38.75 +0.12 26.833333333333336 +0.14 0.0 +0.16 14.133333333333333 +0.18 19.5 +0.2 1.0 +0.22 0.8 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 14.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 3.666666666666667 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-vmeasure.avg.actual b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-vmeasure.avg.actual new file mode 100644 index 00000000..ab72dd95 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-vmeasure.avg.actual @@ -0,0 +1,51 @@ +# similarity error_count +0.0 148.0 +0.02 0.0 +0.04 173.0 +0.06 232.0 +0.08 103.0 +0.1 60.0 +0.12 54.0 +0.14 0.0 +0.16 16.0 +0.18 88.0 +0.2 8.0 +0.22 0.0 +0.24 0.0 +0.26 0.0 +0.28 0.0 +0.3 27.0 +0.32 0.0 +0.34 0.0 +0.36 0.0 +0.38 0.0 +0.4 0.0 +0.42 0.0 +0.44 0.0 +0.46 0.0 +0.48 0.0 +0.5 0.0 +0.52 0.0 +0.54 0.0 +0.56 0.0 +0.58 0.0 +0.6 0.0 +0.62 0.0 +0.64 0.0 +0.66 0.0 +0.68 0.0 +0.7000000000000001 0.0 +0.72 0.0 +0.74 0.0 +0.76 0.0 +0.78 0.0 +0.8 6.0 +0.8200000000000001 0.0 +0.84 0.0 +0.86 0.0 +0.88 0.0 +0.9 0.0 +0.92 0.0 +0.9400000000000001 0.0 +0.96 0.0 +0.98 0.0 diff --git a/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-vmeasure.avg.baseline b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-vmeasure.avg.baseline new file mode 100644 index 00000000..b1dfabea --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/code/plots/semEval-2010-vmeasure.avg.baseline @@ -0,0 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def +/S8 {BL [] 0 setdash 2 copy vpt sub vpt Square fill Bsquare} bind def +/S9 {BL [] 0 setdash 2 copy vpt sub vpt vpt2 Rec fill Bsquare} bind def +/S10 {BL [] 0 setdash 2 copy vpt sub vpt Square fill 2 copy exch vpt sub exch vpt Square fill + Bsquare} bind def +/S11 {BL [] 0 setdash 2 copy vpt sub vpt Square fill 2 copy exch vpt sub exch vpt2 vpt Rec fill + Bsquare} bind def +/S12 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt2 vpt Rec fill Bsquare} bind def +/S13 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt2 vpt Rec fill + 2 copy vpt Square fill Bsquare} bind def +/S14 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt2 vpt Rec fill + 2 copy exch vpt sub exch vpt Square fill Bsquare} bind def +/S15 {BL [] 0 setdash 2 copy Bsquare fill Bsquare} bind def +/D0 {gsave translate 45 rotate 0 0 S0 stroke grestore} bind def +/D1 {gsave translate 45 rotate 0 0 S1 stroke grestore} bind def +/D2 {gsave translate 45 rotate 0 0 S2 stroke grestore} bind def +/D3 {gsave translate 45 rotate 0 0 S3 stroke grestore} bind def +/D4 {gsave translate 45 rotate 0 0 S4 stroke grestore} bind def +/D5 {gsave translate 45 rotate 0 0 S5 stroke grestore} bind def +/D6 {gsave translate 45 rotate 0 0 S6 stroke grestore} bind def +/D7 {gsave translate 45 rotate 0 0 S7 stroke grestore} bind def +/D8 {gsave translate 45 rotate 0 0 S8 stroke grestore} bind def +/D9 {gsave translate 45 rotate 0 0 S9 stroke grestore} bind def +/D10 {gsave translate 45 rotate 0 0 S10 stroke grestore} bind def +/D11 {gsave translate 45 rotate 0 0 S11 stroke grestore} bind def +/D12 {gsave translate 45 rotate 0 0 S12 stroke grestore} bind def +/D13 {gsave translate 45 rotate 0 0 S13 stroke grestore} bind def +/D14 {gsave translate 45 rotate 0 0 S14 stroke grestore} bind def +/D15 {gsave translate 45 rotate 0 0 S15 stroke grestore} bind def +/DiaE {stroke [] 0 setdash vpt add M + hpt neg vpt neg V hpt vpt neg V + hpt vpt V hpt neg vpt V closepath stroke} def +/BoxE {stroke [] 0 setdash exch hpt sub exch vpt add M + 0 vpt2 neg V hpt2 0 V 0 vpt2 V + hpt2 neg 0 V closepath stroke} def +/TriUE {stroke [] 0 setdash vpt 1.12 mul add M + hpt neg vpt -1.62 mul V + hpt 2 mul 0 V + hpt neg vpt 1.62 mul V closepath stroke} def +/TriDE {stroke [] 0 setdash vpt 1.12 mul sub M + hpt neg vpt 1.62 mul V + hpt 2 mul 0 V + hpt neg vpt -1.62 mul V closepath stroke} def +/PentE {stroke [] 0 setdash gsave + translate 0 hpt M 4 {72 rotate 0 hpt L} repeat + closepath stroke grestore} def +/CircE {stroke [] 0 setdash + hpt 0 360 arc stroke} def +/Opaque {gsave closepath 1 setgray fill grestore 0 setgray closepath} def +/DiaW {stroke [] 0 setdash vpt add M + hpt neg vpt neg V hpt vpt neg V + hpt vpt V hpt neg vpt V Opaque stroke} def +/BoxW {stroke [] 0 setdash exch hpt sub exch vpt add M + 0 vpt2 neg V hpt2 0 V 0 vpt2 V + hpt2 neg 0 V Opaque stroke} def +/TriUW {stroke [] 0 setdash vpt 1.12 mul add M + hpt neg vpt -1.62 mul V + hpt 2 mul 0 V + hpt neg vpt 1.62 mul V Opaque stroke} def +/TriDW {stroke [] 0 setdash vpt 1.12 mul sub M + hpt neg vpt 1.62 mul V + hpt 2 mul 0 V + hpt neg vpt -1.62 mul V Opaque stroke} def +/PentW {stroke [] 0 setdash gsave + translate 0 hpt M 4 {72 rotate 0 hpt L} repeat + Opaque stroke grestore} def +/CircW {stroke [] 0 setdash + hpt 0 360 arc Opaque stroke} def +/BoxFill {gsave Rec 1 setgray fill grestore} def +/Density { + /Fillden exch def + currentrgbcolor + /ColB exch def /ColG exch def /ColR exch def + /ColR ColR Fillden mul Fillden sub 1 add def + /ColG ColG Fillden mul Fillden sub 1 add def + /ColB ColB Fillden mul Fillden sub 1 add def + ColR ColG ColB setrgbcolor} def +/BoxColFill {gsave Rec PolyFill} def +/PolyFill {gsave Density fill grestore grestore} def +/h {rlineto rlineto rlineto gsave closepath fill grestore} bind def +% +% PostScript Level 1 Pattern Fill routine for rectangles +% Usage: x y w h s a XX PatternFill +% x,y = lower left corner of box to be filled +% w,h = width and height of box +% a = angle in degrees between lines and x-axis +% XX = 0/1 for no/yes cross-hatch +% +/PatternFill {gsave /PFa [ 9 2 roll ] def + PFa 0 get PFa 2 get 2 div add PFa 1 get PFa 3 get 2 div add translate + PFa 2 get -2 div PFa 3 get -2 div PFa 2 get PFa 3 get Rec + gsave 1 setgray fill grestore clip + currentlinewidth 0.5 mul setlinewidth + /PFs PFa 2 get dup mul PFa 3 get dup mul add sqrt def + 0 0 M PFa 5 get rotate PFs -2 div dup translate + 0 1 PFs PFa 4 get div 1 add floor cvi + {PFa 4 get mul 0 M 0 PFs V} for + 0 PFa 6 get ne { + 0 1 PFs PFa 4 get div 1 add floor cvi + {PFa 4 get mul 0 2 1 roll M PFs 0 V} for + } if + stroke grestore} def +% +/languagelevel where + {pop languagelevel} {1} ifelse + 2 lt + {/InterpretLevel1 true def} + {/InterpretLevel1 Level1 def} + ifelse +% +% PostScript level 2 pattern fill definitions +% +/Level2PatternFill { +/Tile8x8 {/PaintType 2 /PatternType 1 /TilingType 1 /BBox [0 0 8 8] /XStep 8 /YStep 8} + bind def +/KeepColor {currentrgbcolor [/Pattern /DeviceRGB] setcolorspace} bind def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 0 M 8 8 L 0 8 M 8 0 L stroke} +>> matrix makepattern +/Pat1 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 0 M 8 8 L 0 8 M 8 0 L stroke + 0 4 M 4 8 L 8 4 L 4 0 L 0 4 L stroke} +>> matrix makepattern +/Pat2 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 0 M 0 8 L + 8 8 L 8 0 L 0 0 L fill} +>> matrix makepattern +/Pat3 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -4 8 M 8 -4 L + 0 12 M 12 0 L stroke} +>> matrix makepattern +/Pat4 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -4 0 M 8 12 L + 0 -4 M 12 8 L stroke} +>> matrix makepattern +/Pat5 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -2 8 M 4 -4 L + 0 12 M 8 -4 L 4 12 M 10 0 L stroke} +>> matrix makepattern +/Pat6 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -2 0 M 4 12 L + 0 -4 M 8 12 L 4 -4 M 10 8 L stroke} +>> matrix makepattern +/Pat7 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 8 -2 M -4 4 L + 12 0 M -4 8 L 12 4 M 0 10 L stroke} +>> matrix makepattern +/Pat8 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 -2 M 12 4 L + -4 0 M 12 8 L -4 4 M 8 10 L stroke} +>> matrix makepattern +/Pat9 exch def +/Pattern1 {PatternBgnd KeepColor Pat1 setpattern} bind def +/Pattern2 {PatternBgnd KeepColor Pat2 setpattern} bind def +/Pattern3 {PatternBgnd KeepColor Pat3 setpattern} bind def +/Pattern4 {PatternBgnd KeepColor Landscape {Pat5} {Pat4} ifelse setpattern} bind def +/Pattern5 {PatternBgnd KeepColor Landscape {Pat4} {Pat5} ifelse setpattern} bind def +/Pattern6 {PatternBgnd KeepColor Landscape {Pat9} {Pat6} ifelse setpattern} bind def +/Pattern7 {PatternBgnd KeepColor Landscape {Pat8} {Pat7} ifelse setpattern} bind def +} def +% +% +%End of PostScript Level 2 code +% +/PatternBgnd { + TransparentPatterns {} {gsave 1 setgray fill grestore} ifelse +} def +% +% Substitute for Level 2 pattern fill codes with +% grayscale if Level 2 support is not selected. +% +/Level1PatternFill { +/Pattern1 {0.250 Density} bind def +/Pattern2 {0.500 Density} bind def +/Pattern3 {0.750 Density} bind def +/Pattern4 {0.125 Density} bind def +/Pattern5 {0.375 Density} bind def +/Pattern6 {0.625 Density} bind def +/Pattern7 {0.875 Density} bind def +} def +% +% Now test for support of Level 2 code +% +Level1 {Level1PatternFill} {Level2PatternFill} ifelse +% +/Symbol-Oblique /Symbol findfont [1 0 .167 1 0 0] makefont +dup length dict begin {1 index /FID eq {pop pop} {def} ifelse} forall +currentdict end definefont pop +/MFshow { + { dup 5 get 3 ge + { 5 get 3 eq {gsave} {grestore} ifelse } + {dup dup 0 get findfont exch 1 get scalefont setfont + [ currentpoint ] exch dup 2 get 0 exch R dup 5 get 2 ne {dup dup 6 + get exch 4 get {Gshow} {stringwidth pop 0 R} ifelse }if dup 5 get 0 eq + {dup 3 get {2 get neg 0 exch R pop} {pop aload pop M} ifelse} {dup 5 + get 1 eq {dup 2 get exch dup 3 get exch 6 get stringwidth pop -2 div + dup 0 R} {dup 6 get stringwidth pop -2 div 0 R 6 get + show 2 index {aload pop M neg 3 -1 roll neg R pop pop} {pop pop pop + pop aload pop M} ifelse }ifelse }ifelse } + ifelse } + forall} def +/Gswidth {dup type /stringtype eq {stringwidth} {pop (n) stringwidth} ifelse} def +/MFwidth {0 exch { dup 5 get 3 ge { 5 get 3 eq { 0 } { pop } ifelse } + {dup 3 get{dup dup 0 get findfont exch 1 get scalefont setfont + 6 get Gswidth pop add} {pop} ifelse} ifelse} forall} def +/MLshow { currentpoint stroke M + 0 exch R + Blacktext {gsave 0 setgray MFshow grestore} {MFshow} ifelse } bind def +/MRshow { currentpoint stroke M + exch dup MFwidth neg 3 -1 roll R + Blacktext {gsave 0 setgray MFshow grestore} {MFshow} ifelse } bind def +/MCshow { currentpoint stroke M + exch dup MFwidth -2 div 3 -1 roll R + Blacktext {gsave 0 setgray MFshow grestore} {MFshow} ifelse } bind def +/XYsave { [( ) 1 2 true false 3 ()] } bind def +/XYrestore { [( ) 1 2 true false 4 ()] } bind def +end +%%EndProlog +gnudict begin +gsave +doclip +50 50 translate +0.050 0.050 scale +0 setgray +newpath +(Helvetica) findfont 240 scalefont setfont +1.000 UL +LTb +935 2772 M +63 0 V +2457 0 R +-63 0 V +stroke +791 2772 M +[ [(Helvetica) 240.0 0.0 true true 0 (0.00)] +] -80.0 MRshow +1.000 UL +LTb +935 3066 M +63 0 V +2457 0 R +-63 0 V +stroke +791 3066 M +[ [(Helvetica) 240.0 0.0 true true 0 (0.05)] +] -80.0 MRshow +1.000 UL +LTb +935 3360 M +63 0 V +2457 0 R +-63 0 V +stroke +791 3360 M +[ [(Helvetica) 240.0 0.0 true true 0 (0.10)] +] -80.0 MRshow +1.000 UL +LTb +935 3654 M +63 0 V +2457 0 R +-63 0 V +stroke +791 3654 M +[ [(Helvetica) 240.0 0.0 true true 0 (0.15)] +] -80.0 MRshow +1.000 UL +LTb +935 3947 M +63 0 V +2457 0 R +-63 0 V +stroke +791 3947 M +[ [(Helvetica) 240.0 0.0 true true 0 (0.20)] +] -80.0 MRshow +1.000 UL +LTb +935 4241 M +63 0 V +2457 0 R +-63 0 V +stroke +791 4241 M +[ [(Helvetica) 240.0 0.0 true true 0 (0.25)] +] -80.0 MRshow +1.000 UL +LTb +935 4535 M +63 0 V +2457 0 R +-63 0 V +stroke +791 4535 M +[ [(Helvetica) 240.0 0.0 true true 0 (0.30)] +] -80.0 MRshow +1.000 UL +LTb +935 2772 M +0 63 V +0 1700 R +0 -63 V +1250 2772 M +0 63 V +0 1700 R +0 -63 V +1565 2772 M +0 63 V +0 1700 R +0 -63 V +1880 2772 M +0 63 V +0 1700 R +0 -63 V +2195 2772 M +0 63 V +0 1700 R +0 -63 V +2510 2772 M +0 63 V +0 1700 R +0 -63 V +2825 2772 M +0 63 V +0 1700 R +0 -63 V +3140 2772 M +0 63 V +0 1700 R +0 -63 V +3455 2772 M +0 63 V +0 1700 R +0 -63 V +stroke +935 4535 N +0 -1763 V +2520 0 V +0 1763 V +-2520 0 V +Z stroke +LCb setrgbcolor +-49 3653 M +currentpoint gsave translate -270 rotate 0 0 moveto +[ [(Helvetica) 240.0 0.0 true true 0 (V-Measure)] +] -80.0 MCshow +grestore +LTb +2195 4895 M +[ [(Helvetica) 240.0 0.0 true true 0 (ukWaC)] +] -80.0 MCshow +2.000 UP +1.000 UL +LTb +% Begin plot #1 +2.000 UP +1.000 UL +LT0 +1.00 0.00 0.00 C 935 3648 M +315 29 V +315 -6 V +315 6 V +315 -12 V +315 0 V +315 -23 V +315 6 V +315 0 V +935 3648 Star +1250 3677 Star +1565 3671 Star +1880 3677 Star +2195 3665 Star +2510 3665 Star +2825 3642 Star +3140 3648 Star +3455 3648 Star +% End plot #1 +% Begin plot #2 +2.000 UP +1.000 UL +LT1 +0.00 1.00 0.00 C 935 3507 M +315 23 V +315 -18 V +315 24 V +315 -6 V +315 -23 V +315 5 V +315 -11 V +315 35 V +935 3507 TriDF +1250 3530 TriDF +1565 3512 TriDF +1880 3536 TriDF +2195 3530 TriDF +2510 3507 TriDF +2825 3512 TriDF +3140 3501 TriDF +3455 3536 TriDF +% End plot #2 +% Begin plot #3 +2.000 UP +1.000 UL +LT2 +1.00 0.65 0.00 C 935 4241 M +315 18 V +315 -12 V +315 -29 V +315 23 V +315 6 V +315 -59 V +315 6 V +315 0 V +935 4241 Dia +1250 4259 Dia +1565 4247 Dia +1880 4218 Dia +2195 4241 Dia +2510 4247 Dia +2825 4188 Dia +3140 4194 Dia +3455 4194 Dia +% End plot #3 +% Begin plot #4 +2.000 UP +1.000 UL +LT3 +0.75 0.50 1.00 C 935 3354 M +315 -53 V +315 -12 V +315 -53 V +315 -23 V +315 -41 V +315 17 V +315 -12 V +315 -64 V +935 3354 DiaF +1250 3301 DiaF +1565 3289 DiaF +1880 3236 DiaF +2195 3213 DiaF +2510 3172 DiaF +2825 3189 DiaF +3140 3177 DiaF +3455 3113 DiaF +% End plot #4 +1.000 UL +LTb +935 4535 N +0 -1763 V +2520 0 V +0 1763 V +-2520 0 V +Z stroke +2.000 UP +1.000 UL +LTb +1.000 UL +LTb +3960 2772 M +63 0 V +2456 0 R +-63 0 V +3960 3066 M +63 0 V +2456 0 R +-63 0 V +3960 3360 M +63 0 V +2456 0 R +-63 0 V +3960 3654 M +63 0 V +2456 0 R +-63 0 V +3960 3947 M +63 0 V +2456 0 R +-63 0 V +3960 4241 M +63 0 V +2456 0 R +-63 0 V +3960 4535 M +63 0 V +2456 0 R +-63 0 V +3960 2772 M +0 63 V +0 1700 R +0 -63 V +4380 2772 M +0 63 V +0 1700 R +0 -63 V +4800 2772 M +0 63 V +0 1700 R +0 -63 V +5220 2772 M +0 63 V +0 1700 R +0 -63 V +5639 2772 M +0 63 V +0 1700 R +0 -63 V +6059 2772 M +0 63 V +0 1700 R +0 -63 V +6479 2772 M +0 63 V +0 1700 R +0 -63 V +stroke +3960 4535 N +0 -1763 V +2519 0 V +0 1763 V +-2519 0 V +Z stroke +5219 4895 M +[ [(Helvetica) 240.0 0.0 true true 0 (Wikipedia)] +] -80.0 MCshow +2.000 UP +1.000 UL +LTb +% Begin plot #1 +2.000 UP +1.000 UL +LT0 +1.00 0.00 0.00 C 3960 3677 M +420 -12 V +420 -53 V +420 94 V +419 -23 V +420 6 V +420 23 V +3960 3677 Star +4380 3665 Star +4800 3612 Star +5220 3706 Star +5639 3683 Star +6059 3689 Star +6479 3712 Star +% End plot #1 +% Begin plot #2 +2.000 UP +1.000 UL +LT1 +0.00 1.00 0.00 C 3960 3536 M +420 6 V +420 -30 V +420 12 V +419 -17 V +420 35 V +420 -47 V +3960 3536 TriDF +4380 3542 TriDF +4800 3512 TriDF +5220 3524 TriDF +5639 3507 TriDF +6059 3542 TriDF +6479 3495 TriDF +% End plot #2 +% Begin plot #3 +2.000 UP +1.000 UL +LT2 +1.00 0.65 0.00 C 3960 4247 M +420 18 V +420 -77 V +420 12 V +419 29 V +420 -52 V +6479 2772 L +3960 4247 Dia +4380 4265 Dia +4800 4188 Dia +5220 4200 Dia +5639 4229 Dia +6059 4177 Dia +6479 2772 Dia +% End plot #3 +% Begin plot #4 +2.000 UP +1.000 UL +LT3 +0.75 0.50 1.00 C 3960 2772 M +420 488 V +420 41 V +420 -76 V +419 -12 V +420 -30 V +420 -6 V +3960 2772 DiaF +4380 3260 DiaF +4800 3301 DiaF +5220 3225 DiaF +5639 3213 DiaF +6059 3183 DiaF +6479 3177 DiaF +% End plot #4 +1.000 UL +LTb +3960 4535 N +0 -1763 V +2519 0 V +0 1763 V +-2519 0 V +Z stroke +2.000 UP +1.000 UL +LTb +1.000 UL +LTb +935 655 M +63 0 V +2457 0 R +-63 0 V +stroke +791 655 M +[ [(Helvetica) 240.0 0.0 true true 0 ( 0.00)] +] -80.0 MRshow +1.000 UL +LTb +935 876 M +63 0 V +2457 0 R +-63 0 V +stroke +791 876 M +[ [(Helvetica) 240.0 0.0 true true 0 ( 0.10)] +] -80.0 MRshow +1.000 UL +LTb +935 1096 M +63 0 V +2457 0 R +-63 0 V +stroke +791 1096 M +[ [(Helvetica) 240.0 0.0 true true 0 ( 0.20)] +] -80.0 MRshow +1.000 UL +LTb +935 1317 M +63 0 V +2457 0 R +-63 0 V +stroke +791 1317 M +[ [(Helvetica) 240.0 0.0 true true 0 ( 0.30)] +] -80.0 MRshow +1.000 UL +LTb +935 1537 M +63 0 V +2457 0 R +-63 0 V +stroke +791 1537 M +[ [(Helvetica) 240.0 0.0 true true 0 ( 0.40)] +] -80.0 MRshow +1.000 UL +LTb +935 1758 M +63 0 V +2457 0 R +-63 0 V +stroke +791 1758 M +[ [(Helvetica) 240.0 0.0 true true 0 ( 0.50)] +] -80.0 MRshow +1.000 UL +LTb +935 1978 M +63 0 V +2457 0 R +-63 0 V +stroke +791 1978 M +[ [(Helvetica) 240.0 0.0 true true 0 ( 0.60)] +] -80.0 MRshow +1.000 UL +LTb +935 2199 M +63 0 V +2457 0 R +-63 0 V +stroke +791 2199 M +[ [(Helvetica) 240.0 0.0 true true 0 ( 0.70)] +] -80.0 MRshow +1.000 UL +LTb +935 2419 M +63 0 V +2457 0 R +-63 0 V +stroke +791 2419 M +[ [(Helvetica) 240.0 0.0 true true 0 ( 0.80)] +] -80.0 MRshow +1.000 UL +LTb +935 655 M +0 63 V +0 1701 R +0 -63 V +stroke +935 415 M +[ [(Helvetica) 240.0 0.0 true true 0 ( 0)] +] -80.0 MCshow +1.000 UL +LTb +1250 655 M +0 63 V +0 1701 R +0 -63 V +stroke +1250 415 M +[ [(Helvetica) 240.0 0.0 true true 0 ( 1)] +] -80.0 MCshow +1.000 UL +LTb +1565 655 M +0 63 V +0 1701 R +0 -63 V +stroke +1565 415 M +[ [(Helvetica) 240.0 0.0 true true 0 ( 2)] +] -80.0 MCshow +1.000 UL +LTb +1880 655 M +0 63 V +0 1701 R +0 -63 V +stroke +1880 415 M +[ [(Helvetica) 240.0 0.0 true true 0 ( 3)] +] -80.0 MCshow +1.000 UL +LTb +2195 655 M +0 63 V +0 1701 R +0 -63 V +stroke +2195 415 M +[ [(Helvetica) 240.0 0.0 true true 0 ( 4)] +] -80.0 MCshow +1.000 UL +LTb +2510 655 M +0 63 V +0 1701 R +0 -63 V +stroke +2510 415 M +[ [(Helvetica) 240.0 0.0 true true 0 ( 5)] +] -80.0 MCshow +1.000 UL +LTb +2825 655 M +0 63 V +0 1701 R +0 -63 V +stroke +2825 415 M +[ [(Helvetica) 240.0 0.0 true true 0 ( 6)] +] -80.0 MCshow +1.000 UL +LTb +3140 655 M +0 63 V +0 1701 R +0 -63 V +stroke +3140 415 M +[ [(Helvetica) 240.0 0.0 true true 0 ( 7)] +] -80.0 MCshow +1.000 UL +LTb +3455 655 M +0 63 V +0 1701 R +0 -63 V +stroke +3455 415 M +[ [(Helvetica) 240.0 0.0 true true 0 ( 8)] +] -80.0 MCshow +1.000 UL +LTb +1.000 UL +LTb +935 2419 N +935 655 L +2520 0 V +0 1764 V +-2520 0 V +Z stroke +LCb setrgbcolor +-193 1537 M +currentpoint gsave translate -270 rotate 0 0 moveto +[ [(Helvetica) 240.0 0.0 true true 0 (Paired FScore)] +] -80.0 MCshow +grestore +LTb +LCb setrgbcolor +2195 55 M +[ [(Helvetica) 240.0 0.0 true true 0 (Segment Number)] +] -80.0 MCshow +LTb +2.000 UP +1.000 UL +LTb +% Begin plot #1 +2.000 UP +1.000 UL +LT0 +1.00 0.00 0.00 C 935 1186 M +315 -3 V +315 7 V +315 -15 V +315 8 V +315 -8 V +315 100 V +315 -13 V +315 1 V +935 1186 Star +1250 1183 Star +1565 1190 Star +1880 1175 Star +2195 1183 Star +2510 1175 Star +2825 1275 Star +3140 1262 Star +3455 1263 Star +% End plot #1 +% Begin plot #2 +2.000 UP +1.000 UL +LT1 +0.00 1.00 0.00 C 935 1383 M +315 32 V +315 9 V +315 24 V +315 13 V +315 -25 V +315 -32 V +315 37 V +315 13 V +935 1383 TriDF +1250 1415 TriDF +1565 1424 TriDF +1880 1448 TriDF +2195 1461 TriDF +2510 1436 TriDF +2825 1404 TriDF +3140 1441 TriDF +3455 1454 TriDF +% End plot #2 +% Begin plot #3 +2.000 UP +1.000 UL +LT2 +1.00 0.65 0.00 C 935 879 M +315 -1 V +315 -12 V +315 17 V +315 -9 V +315 -7 V +315 119 V +315 5 V +315 0 V +935 879 Dia +1250 878 Dia +1565 866 Dia +1880 883 Dia +2195 874 Dia +2510 867 Dia +2825 986 Dia +3140 991 Dia +3455 991 Dia +% End plot #3 +% Begin plot #4 +2.000 UP +1.000 UL +LT3 +0.75 0.50 1.00 C 935 1744 M +315 -37 V +315 4 V +315 97 V +315 -9 V +315 2 V +315 79 V +315 36 V +315 -8 V +935 1744 DiaF +1250 1707 DiaF +1565 1711 DiaF +1880 1808 DiaF +2195 1799 DiaF +2510 1801 DiaF +2825 1880 DiaF +3140 1916 DiaF 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true 0 ( 3)] +] -80.0 MCshow +1.000 UL +LTb +5639 655 M +0 63 V +0 1701 R +0 -63 V +stroke +5639 415 M +[ [(Helvetica) 240.0 0.0 true true 0 ( 4)] +] -80.0 MCshow +1.000 UL +LTb +6059 655 M +0 63 V +0 1701 R +0 -63 V +stroke +6059 415 M +[ [(Helvetica) 240.0 0.0 true true 0 ( 5)] +] -80.0 MCshow +1.000 UL +LTb +6479 655 M +0 63 V +0 1701 R +0 -63 V +stroke +6479 415 M +[ [(Helvetica) 240.0 0.0 true true 0 ( 6)] +] -80.0 MCshow +1.000 UL +LTb +1.000 UL +LTb +3960 2419 N +0 -1764 V +2519 0 V +0 1764 V +-2519 0 V +Z stroke +LCb setrgbcolor +5219 55 M +[ [(Helvetica) 240.0 0.0 true true 0 (Segment Number)] +] -80.0 MCshow +LTb +2.000 UP +1.000 UL +LTb +% Begin plot #1 +2.000 UP +1.000 UL +LT0 +1.00 0.00 0.00 C 3960 1178 M +420 -2 V +420 29 V +420 -22 V +419 -15 V +420 1 V +420 3 V +3960 1178 Star +4380 1176 Star +4800 1205 Star +5220 1183 Star +5639 1168 Star +6059 1169 Star +6479 1172 Star +% End plot #1 +% Begin plot #2 +2.000 UP +1.000 UL +LT1 +0.00 1.00 0.00 C 3960 1406 M +420 11 V 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b/papers/2011_emnlp_unsup_impact/figures/cooccurrence-results.p new file mode 100644 index 00000000..560efb00 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/cooccurrence-results.p @@ -0,0 +1,85 @@ +set term postscript eps enhanced color lw 3 "Helvetica" 24 +set output 'cooccurrence-results.eps' +#set terminal png transparent nocrop enhanced font arial 8 size 500,350 +#set output 'cooccurrence-results.png' + +set pointsize 2 +set multiplot +set size 0.35,0.35 + +# FIXME: the key needs to go at the bottom of all the plots +unset key +#set key outside bottom center vertical noreverse enhanced autotitles nobox + +set xtics mirror +set format x "%2.0f" +set format y "%.2f" + +set yrange [ 0.0 : 0.30 ] noreverse nowriteback +set ylabel "V-Measure" +set format x '' +set title "ukWaC" + +set lmargin 0 +set rmargin 0 +set bmargin 0 +set tmargin 0 +set origin 0.13, 0.55 + +# UKWAC data +plot 'dv-wc-wordsi-scores-ukwac.dat' using 1:3 title "K-Means V-Measure" ls 2 pt 3 lw 1 lc rgb "red" lt 1 axis x1y1 with linespoints, \ + 'dv-wc-wordsi-scores-ukwac.dat' using 1:5 title "Spectra V-Measure" ls 2 pt 11 lw 1 lc rgb "green" lt 2 axis x1y1 with linespoints, \ + 'dv-wc-wordsi-scores-ukwac.dat' using 1:7 title "CBC V-Measure" ls 2 pt 12 lw 1 lc rgb "orange" lt 3 axis x1y1 with linespoints, \ + 'dv-wc-wordsi-scores-ukwac.dat' using 1:9 title "On-line K-Means V-Measure" ls 2 pt 13 lw 1 lc rgb "purple" lt 4 axis x1y1 with linespoints + +unset ylabel +set format y '' +set title "Wikipedia" +set origin 0.55, 0.55 + +# WIKIPEDIA +plot 'dv-wc-wordsi-scores-wiki.dat' using 1:3 title "K-Means V-Measure" ls 2 pt 3 lw 1 lc rgb "red" lt 1 axis x1y1 with linespoints, \ + 'dv-wc-wordsi-scores-wiki.dat' using 1:5 title "Spectra V-Measure" ls 2 pt 11 lw 1 lc rgb "green" lt 2 axis x1y1 with linespoints, \ + 'dv-wc-wordsi-scores-wiki.dat' using 1:7 title "CBC V-Measure" ls 2 pt 12 lw 1 lc rgb "orange" lt 3 axis x1y1 with linespoints, \ + 'dv-wc-wordsi-scores-wiki.dat' using 1:9 title "On-line K-Means V-Measure" ls 2 pt 13 lw 1 lc rgb "purple" lt 4 axis x1y1 with linespoints + +# remove the ukWaC and Wikipedia titles for the lower graphs +unset title +# add the xtic labeling back +set format x ' %g' +set format y ' %.2f' + +set xtics auto +set ylabel "Paired FScore" +set xlabel 'Segment Number' +# NOTE: this range should stay fixed across all result plots +# to ensure horizontal readability +set yrange [ 0.0 : 0.80 ] noreverse nowriteback + + +#set xrange [ 0 : 8 ] noreverse nowriteback +set ytics auto + +set origin 0.13, 0.13 + +# UKWAC +plot 'dv-wc-wordsi-scores-ukwac.dat' using 1:2 title "K-Means F-Score" ls 1 pt 3 lw 1 lc rgb "red" lt 1 axis x1y1 with linespoints, \ + 'dv-wc-wordsi-scores-ukwac.dat' using 1:4 title "Spectral F-Score" ls 1 pt 11 lw 1 lc rgb "green" lt 2 axis x1y1 with linespoints, \ + 'dv-wc-wordsi-scores-ukwac.dat' using 1:6 title "CBC F-Score" ls 1 pt 12 lw 1 lc rgb "orange" lt 3 axis x1y1 with linespoints, \ + 'dv-wc-wordsi-scores-ukwac.dat' using 1:8 title "On-line K-Means F-Score" ls 1 pt 13 lw 1 lc rgb "purple" lt 4 axis x1y1 with linespoints + +unset ylabel +set format y '' +set origin 0.55, 0.13 + +# WIKIPEDIA +plot 'dv-wc-wordsi-scores-wiki.dat' using 1:2 title "K-Means F-Score" ls 1 pt 3 lw 1 lc rgb "red" lt 1 axis x1y1 with linespoints, \ + 'dv-wc-wordsi-scores-wiki.dat' using 1:4 title "Spectral F-Score" ls 1 pt 11 lw 1 lc rgb "green" lt 2 axis x1y1 with linespoints, \ + 'dv-wc-wordsi-scores-wiki.dat' using 1:6 title "CBC F-Score" ls 1 pt 12 lw 1 lc rgb "orange" lt 3 axis x1y1 with linespoints, \ + 'dv-wc-wordsi-scores-wiki.dat' using 1:8 title "On-line K-Means F-Score" ls 1 pt 13 lw 1 lc rgb "purple" lt 4 axis x1y1 with linespoints + + + + + + diff --git a/papers/2011_emnlp_unsup_impact/figures/cooccurrence-results.png b/papers/2011_emnlp_unsup_impact/figures/cooccurrence-results.png new file mode 100644 index 00000000..e86b41e9 Binary files /dev/null and b/papers/2011_emnlp_unsup_impact/figures/cooccurrence-results.png differ diff --git a/papers/2011_emnlp_unsup_impact/figures/cooccurrence-results2.p b/papers/2011_emnlp_unsup_impact/figures/cooccurrence-results2.p new file mode 100644 index 00000000..b48a28b3 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/cooccurrence-results2.p @@ -0,0 +1,39 @@ +#set term postscript eps enhanced color lw 3 "Helvetica" 24 +#set output 'cooccurrence-results.eps' +set terminal png transparent nocrop enhanced font arial 8 size 500,350 +set output 'cooccurrence-results.png' + +set xtics mirror +set format x "%2.0f" +set format y "%.2f" +set format y2 "%.2f" + +# move the key out of the way +set key outside bottom center vertical noreverse enhanced autotitles nobox + +set ylabel "F-Score" +set y2label "V-Measure" +set xlabel 'Segment Number' +set yrange [ 0.25 : 0.80 ] noreverse nowriteback +set y2range [ 0.0 : 0.30 ] noreverse nowriteback +#set ytics 0,.1 + +set xrange [ 1 : 8 ] noreverse nowriteback +set y2tics auto +set ytics auto nomirror + +plot 'cooccurrence-scores-ukwac.dat' using 1:2 title "K-Means F-Score" ls 1 pt 4 lw 1 lc rgb "red" axis x1y1 with linespoints, \ + 'cooccurrence-scores-ukwac.dat' using 1:3 title "K-Means V-Measure" ls 2 pt 9 lw 1 lc rgb "red" lt 2 axis x1y2 with linespoints, \ + 'cooccurrence-scores-ukwac.dat' using 1:4 title "Agglomerative F-Score" ls 1 pt 4 lw 1 lc rgb "blue" axis x1y1 with linespoints, \ + 'cooccurrence-scores-ukwac.dat' using 1:5 title "Agglomerative V-Measure" ls 2 pt 9 lw 1 lc rgb "blue" lt 2 axis x1y2 with linespoints, \ + 'cooccurrence-scores-ukwac.dat' using 1:6 title "Spectral F-Score" ls 1 pt 4 lw 1 lc rgb "green" axis x1y1 with linespoints, \ + 'cooccurrence-scores-ukwac.dat' using 1:7 title "Spectra V-Measure" ls 2 pt 9 lw 1 lc rgb "green" lt 2 axis x1y2 with linespoints, \ + 'cooccurrence-scores-ukwac.dat' using 1:8 title "CBC F-Score" ls 1 pt 4 lw 1 lc rgb "orange" axis x1y1 with linespoints, \ + 'cooccurrence-scores-ukwac.dat' using 1:9 title "CBC V-Measure" ls 2 pt 9 lw 1 lc rgb "orange" lt 3 axis x1y2 with linespoints, \ + 'cooccurrence-scores-ukwac.dat' using 1:10 title "On-line K-Means F-Score" ls 1 pt 4 lw 1 lc rgb "purple" axis x1y1 with linespoints, \ + 'cooccurrence-scores-ukwac.dat' using 1:11 title "Ob-line K-Means V-Measure" ls 2 pt 9 lw 1 lc rgb "purple" lt 3 axis x1y2 with linespoints + + + + + diff --git a/papers/2011_emnlp_unsup_impact/figures/cooccurrence-scores-ukwac.dat b/papers/2011_emnlp_unsup_impact/figures/cooccurrence-scores-ukwac.dat new file mode 100644 index 00000000..900159b7 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/cooccurrence-scores-ukwac.dat @@ -0,0 +1,9 @@ +# segment k-means-f k-means-v algo-f aglo-v spec-f spec-v cbc-f cbc-v online-f online-v +1 .50 .01 .56 .06 .61 .10 .65 .15 .70 .20 +2 .51 .02 .57 .07 .62 .11 .66 .16 .71 .21 +3 .52 .03 .58 .08 .63 .12 .67 .17 .72 .22 +4 .53 .04 .59 .09 .64 .13 .68 .18 .73 .23 +5 .54 .05 .50 .01 .65 .14 .69 .19 .74 .24 +6 .55 .06 .51 .02 .66 .15 .61 .11 .75 .25 +7 .56 .07 .52 .03 .67 .16 .62 .12 .76 .26 +8 .57 .08 .53 .04 .68 .17 .63 .13 .77 .27 diff --git a/papers/2011_emnlp_unsup_impact/figures/cooccurrence-scores.dat b/papers/2011_emnlp_unsup_impact/figures/cooccurrence-scores.dat new file mode 100644 index 00000000..af9b3130 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/cooccurrence-scores.dat @@ -0,0 +1 @@ +# segment k-means-f k-means-v algo-f aglo-v spec-f spec-v cbc-f cbc-v online-f online-v \ No newline at end of file diff --git a/papers/2011_emnlp_unsup_impact/figures/dv-pwd-results.eps b/papers/2011_emnlp_unsup_impact/figures/dv-pwd-results.eps new file mode 100644 index 00000000..623b608f --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/dv-pwd-results.eps @@ -0,0 +1,870 @@ +%!PS-Adobe-2.0 EPSF-2.0 +%%Title: dv-pwd-results.eps +%%Creator: gnuplot 4.3 patchlevel 0 +%%CreationDate: Fri May 20 20:02:12 2011 +%%DocumentFonts: (atend) 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V + hpt neg vpt 1.62 mul V closepath fill} def +/TriD {stroke [] 0 setdash 2 copy vpt 1.12 mul sub M + hpt neg vpt 1.62 mul V + hpt 2 mul 0 V + hpt neg vpt -1.62 mul V closepath stroke + Pnt} def +/TriDF {stroke [] 0 setdash vpt 1.12 mul sub M + hpt neg vpt 1.62 mul V + hpt 2 mul 0 V + hpt neg vpt -1.62 mul V closepath fill} def +/DiaF {stroke [] 0 setdash vpt add M + hpt neg vpt neg V hpt vpt neg V + hpt vpt V hpt neg vpt V closepath fill} def +/Pent {stroke [] 0 setdash 2 copy gsave + translate 0 hpt M 4 {72 rotate 0 hpt L} repeat + closepath stroke grestore Pnt} def +/PentF {stroke [] 0 setdash gsave + translate 0 hpt M 4 {72 rotate 0 hpt L} repeat + closepath fill grestore} def +/Circle {stroke [] 0 setdash 2 copy + hpt 0 360 arc stroke Pnt} def +/CircleF {stroke [] 0 setdash hpt 0 360 arc fill} def +/C0 {BL [] 0 setdash 2 copy moveto vpt 90 450 arc} bind def +/C1 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 0 90 arc closepath fill + vpt 0 360 arc closepath} bind def +/C2 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 90 180 arc closepath fill + vpt 0 360 arc closepath} bind def +/C3 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 0 180 arc closepath fill + vpt 0 360 arc closepath} bind def +/C4 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 180 270 arc closepath fill + vpt 0 360 arc closepath} bind def +/C5 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 0 90 arc + 2 copy moveto + 2 copy vpt 180 270 arc closepath fill + vpt 0 360 arc} bind def +/C6 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 90 270 arc closepath fill + vpt 0 360 arc closepath} bind def +/C7 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 0 270 arc closepath fill + vpt 0 360 arc closepath} bind def +/C8 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 270 360 arc closepath fill + vpt 0 360 arc closepath} bind def +/C9 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 270 450 arc closepath fill + vpt 0 360 arc closepath} bind def +/C10 {BL [] 0 setdash 2 copy 2 copy moveto vpt 270 360 arc closepath fill + 2 copy moveto + 2 copy vpt 90 180 arc closepath fill + vpt 0 360 arc closepath} bind def +/C11 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 0 180 arc closepath fill + 2 copy moveto + 2 copy vpt 270 360 arc closepath fill + vpt 0 360 arc closepath} bind def +/C12 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 180 360 arc closepath fill + vpt 0 360 arc closepath} bind def +/C13 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 0 90 arc closepath fill + 2 copy moveto + 2 copy vpt 180 360 arc closepath fill + vpt 0 360 arc closepath} bind def +/C14 {BL [] 0 setdash 2 copy moveto + 2 copy vpt 90 360 arc closepath fill + vpt 0 360 arc} bind def +/C15 {BL [] 0 setdash 2 copy vpt 0 360 arc closepath fill + vpt 0 360 arc closepath} bind def +/Rec {newpath 4 2 roll moveto 1 index 0 rlineto 0 exch rlineto + neg 0 rlineto closepath} bind def +/Square {dup Rec} bind def +/Bsquare {vpt sub exch vpt sub exch vpt2 Square} bind def +/S0 {BL [] 0 setdash 2 copy moveto 0 vpt rlineto BL Bsquare} bind def +/S1 {BL [] 0 setdash 2 copy vpt Square fill Bsquare} bind def +/S2 {BL [] 0 setdash 2 copy exch vpt sub exch vpt Square fill Bsquare} bind def +/S3 {BL [] 0 setdash 2 copy exch vpt sub exch vpt2 vpt Rec fill Bsquare} bind def +/S4 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt Square fill Bsquare} bind def +/S5 {BL [] 0 setdash 2 copy 2 copy vpt Square fill + exch vpt sub exch vpt sub vpt Square fill Bsquare} bind def +/S6 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt vpt2 Rec fill Bsquare} bind def +/S7 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt vpt2 Rec fill + 2 copy vpt Square fill Bsquare} bind def +/S8 {BL [] 0 setdash 2 copy vpt sub vpt Square fill Bsquare} bind def +/S9 {BL [] 0 setdash 2 copy vpt sub vpt vpt2 Rec fill Bsquare} bind def +/S10 {BL [] 0 setdash 2 copy vpt sub vpt Square fill 2 copy exch vpt sub exch vpt Square fill + Bsquare} bind def +/S11 {BL [] 0 setdash 2 copy vpt sub vpt Square fill 2 copy exch vpt sub exch vpt2 vpt Rec fill + Bsquare} bind def +/S12 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt2 vpt Rec fill Bsquare} bind def +/S13 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt2 vpt Rec fill + 2 copy vpt Square fill Bsquare} bind def +/S14 {BL [] 0 setdash 2 copy exch vpt sub exch vpt sub vpt2 vpt Rec fill + 2 copy exch vpt sub exch vpt Square fill Bsquare} bind def +/S15 {BL [] 0 setdash 2 copy Bsquare fill Bsquare} bind def +/D0 {gsave translate 45 rotate 0 0 S0 stroke grestore} bind def +/D1 {gsave translate 45 rotate 0 0 S1 stroke grestore} bind def +/D2 {gsave translate 45 rotate 0 0 S2 stroke grestore} bind def +/D3 {gsave translate 45 rotate 0 0 S3 stroke grestore} bind def +/D4 {gsave translate 45 rotate 0 0 S4 stroke grestore} bind def +/D5 {gsave translate 45 rotate 0 0 S5 stroke grestore} bind def +/D6 {gsave translate 45 rotate 0 0 S6 stroke grestore} bind def +/D7 {gsave translate 45 rotate 0 0 S7 stroke grestore} bind def +/D8 {gsave translate 45 rotate 0 0 S8 stroke grestore} bind def +/D9 {gsave translate 45 rotate 0 0 S9 stroke grestore} bind def +/D10 {gsave translate 45 rotate 0 0 S10 stroke grestore} bind def +/D11 {gsave translate 45 rotate 0 0 S11 stroke grestore} bind def +/D12 {gsave translate 45 rotate 0 0 S12 stroke grestore} bind def +/D13 {gsave translate 45 rotate 0 0 S13 stroke grestore} bind def +/D14 {gsave translate 45 rotate 0 0 S14 stroke grestore} bind def +/D15 {gsave translate 45 rotate 0 0 S15 stroke grestore} bind def +/DiaE {stroke [] 0 setdash vpt add M + hpt neg vpt neg V hpt vpt neg V + hpt vpt V hpt neg vpt V closepath stroke} def +/BoxE {stroke [] 0 setdash exch hpt sub exch vpt add M + 0 vpt2 neg V hpt2 0 V 0 vpt2 V + hpt2 neg 0 V closepath stroke} def +/TriUE {stroke [] 0 setdash vpt 1.12 mul add M + hpt neg vpt -1.62 mul V + hpt 2 mul 0 V + hpt neg vpt 1.62 mul V closepath stroke} def +/TriDE {stroke [] 0 setdash vpt 1.12 mul sub M + hpt neg vpt 1.62 mul V + hpt 2 mul 0 V + hpt neg vpt -1.62 mul V closepath stroke} def +/PentE {stroke [] 0 setdash gsave + translate 0 hpt M 4 {72 rotate 0 hpt L} repeat + closepath stroke grestore} def +/CircE {stroke [] 0 setdash + hpt 0 360 arc stroke} def +/Opaque {gsave closepath 1 setgray fill grestore 0 setgray closepath} def +/DiaW {stroke [] 0 setdash vpt add M + hpt neg vpt neg V hpt vpt neg V + hpt vpt V hpt neg vpt V Opaque stroke} def +/BoxW {stroke [] 0 setdash exch hpt sub exch vpt add M + 0 vpt2 neg V hpt2 0 V 0 vpt2 V + hpt2 neg 0 V Opaque stroke} def +/TriUW {stroke [] 0 setdash vpt 1.12 mul add M + hpt neg vpt -1.62 mul V + hpt 2 mul 0 V + hpt neg vpt 1.62 mul V Opaque stroke} def +/TriDW {stroke [] 0 setdash vpt 1.12 mul sub M + hpt neg vpt 1.62 mul V + hpt 2 mul 0 V + hpt neg vpt -1.62 mul V Opaque stroke} def +/PentW {stroke [] 0 setdash gsave + translate 0 hpt M 4 {72 rotate 0 hpt L} repeat + Opaque stroke grestore} def +/CircW {stroke [] 0 setdash + hpt 0 360 arc Opaque stroke} def +/BoxFill {gsave Rec 1 setgray fill grestore} def +/Density { + /Fillden exch def + currentrgbcolor + /ColB exch def /ColG exch def /ColR exch def + /ColR ColR Fillden mul Fillden sub 1 add def + /ColG ColG Fillden mul Fillden sub 1 add def + /ColB ColB Fillden mul Fillden sub 1 add def + ColR ColG ColB setrgbcolor} def +/BoxColFill {gsave Rec PolyFill} def +/PolyFill {gsave Density fill grestore grestore} def +/h {rlineto rlineto rlineto gsave closepath fill grestore} bind def +% +% PostScript Level 1 Pattern Fill routine for rectangles +% Usage: x y w h s a XX PatternFill +% x,y = lower left corner of box to be filled +% w,h = width and height of box +% a = angle in degrees between lines and x-axis +% XX = 0/1 for no/yes cross-hatch +% +/PatternFill {gsave /PFa [ 9 2 roll ] def + PFa 0 get PFa 2 get 2 div add PFa 1 get PFa 3 get 2 div add translate + PFa 2 get -2 div PFa 3 get -2 div PFa 2 get PFa 3 get Rec + gsave 1 setgray fill grestore clip + currentlinewidth 0.5 mul setlinewidth + /PFs PFa 2 get dup mul PFa 3 get dup mul add sqrt def + 0 0 M PFa 5 get rotate PFs -2 div dup translate + 0 1 PFs PFa 4 get div 1 add floor cvi + {PFa 4 get mul 0 M 0 PFs V} for + 0 PFa 6 get ne { + 0 1 PFs PFa 4 get div 1 add floor cvi + {PFa 4 get mul 0 2 1 roll M PFs 0 V} for + } if + stroke grestore} def +% +/languagelevel where + {pop languagelevel} {1} ifelse + 2 lt + {/InterpretLevel1 true def} + {/InterpretLevel1 Level1 def} + ifelse +% +% PostScript level 2 pattern fill definitions +% +/Level2PatternFill { +/Tile8x8 {/PaintType 2 /PatternType 1 /TilingType 1 /BBox [0 0 8 8] /XStep 8 /YStep 8} + bind def +/KeepColor {currentrgbcolor [/Pattern /DeviceRGB] setcolorspace} bind def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 0 M 8 8 L 0 8 M 8 0 L stroke} +>> matrix makepattern +/Pat1 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 0 M 8 8 L 0 8 M 8 0 L stroke + 0 4 M 4 8 L 8 4 L 4 0 L 0 4 L stroke} +>> matrix makepattern +/Pat2 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 0 M 0 8 L + 8 8 L 8 0 L 0 0 L fill} +>> matrix makepattern +/Pat3 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -4 8 M 8 -4 L + 0 12 M 12 0 L stroke} +>> matrix makepattern +/Pat4 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -4 0 M 8 12 L + 0 -4 M 12 8 L stroke} +>> matrix makepattern +/Pat5 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -2 8 M 4 -4 L + 0 12 M 8 -4 L 4 12 M 10 0 L stroke} +>> matrix makepattern +/Pat6 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop -2 0 M 4 12 L + 0 -4 M 8 12 L 4 -4 M 10 8 L stroke} +>> matrix makepattern +/Pat7 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 8 -2 M -4 4 L + 12 0 M -4 8 L 12 4 M 0 10 L stroke} +>> matrix makepattern +/Pat8 exch def +<< Tile8x8 + /PaintProc {0.5 setlinewidth pop 0 -2 M 12 4 L + -4 0 M 12 8 L -4 4 M 8 10 L stroke} +>> matrix makepattern +/Pat9 exch def +/Pattern1 {PatternBgnd KeepColor Pat1 setpattern} bind def +/Pattern2 {PatternBgnd KeepColor Pat2 setpattern} bind def +/Pattern3 {PatternBgnd KeepColor Pat3 setpattern} bind def +/Pattern4 {PatternBgnd KeepColor Landscape {Pat5} {Pat4} ifelse setpattern} bind def +/Pattern5 {PatternBgnd KeepColor Landscape {Pat4} {Pat5} ifelse setpattern} bind def +/Pattern6 {PatternBgnd KeepColor Landscape {Pat9} {Pat6} ifelse setpattern} bind def +/Pattern7 {PatternBgnd KeepColor Landscape {Pat8} {Pat7} ifelse setpattern} bind def +} def +% +% +%End of PostScript Level 2 code +% +/PatternBgnd { + TransparentPatterns {} {gsave 1 setgray fill grestore} ifelse +} def +% +% Substitute for Level 2 pattern fill codes with +% grayscale if Level 2 support is not selected. +% +/Level1PatternFill { +/Pattern1 {0.250 Density} bind def +/Pattern2 {0.500 Density} bind def +/Pattern3 {0.750 Density} bind def +/Pattern4 {0.125 Density} bind def +/Pattern5 {0.375 Density} bind def +/Pattern6 {0.625 Density} bind def +/Pattern7 {0.875 Density} bind def +} def +% +% Now test for support of Level 2 code +% +Level1 {Level1PatternFill} {Level2PatternFill} ifelse +% +/Symbol-Oblique /Symbol findfont [1 0 .167 1 0 0] makefont +dup length dict begin {1 index /FID eq {pop pop} {def} ifelse} forall +currentdict end definefont pop +/MFshow { + { dup 5 get 3 ge + { 5 get 3 eq {gsave} {grestore} ifelse } + {dup dup 0 get findfont exch 1 get scalefont setfont + [ currentpoint ] exch dup 2 get 0 exch R dup 5 get 2 ne {dup dup 6 + get exch 4 get {Gshow} {stringwidth pop 0 R} ifelse }if dup 5 get 0 eq + {dup 3 get {2 get neg 0 exch R pop} {pop aload pop M} ifelse} {dup 5 + get 1 eq {dup 2 get exch dup 3 get exch 6 get stringwidth pop -2 div + dup 0 R} {dup 6 get stringwidth pop -2 div 0 R 6 get + show 2 index {aload pop M neg 3 -1 roll neg R pop pop} {pop pop pop + pop aload pop M} ifelse }ifelse }ifelse } + ifelse } + forall} def +/Gswidth {dup type /stringtype eq {stringwidth} {pop (n) stringwidth} ifelse} def +/MFwidth {0 exch { dup 5 get 3 ge { 5 get 3 eq { 0 } { pop } ifelse } + {dup 3 get{dup dup 0 get findfont exch 1 get scalefont setfont + 6 get Gswidth pop add} {pop} ifelse} ifelse} forall} def +/MLshow { currentpoint stroke M + 0 exch R + Blacktext {gsave 0 setgray MFshow grestore} {MFshow} ifelse } bind def +/MRshow { currentpoint stroke M + exch dup MFwidth neg 3 -1 roll R + Blacktext {gsave 0 setgray MFshow grestore} {MFshow} ifelse } bind def +/MCshow { currentpoint stroke M + exch dup MFwidth -2 div 3 -1 roll R + Blacktext {gsave 0 setgray MFshow grestore} {MFshow} ifelse } bind def +/XYsave { [( ) 1 2 true false 3 ()] } bind def +/XYrestore { [( ) 1 2 true false 4 ()] } bind def +end +%%EndProlog +gnudict begin +gsave +doclip +50 50 translate +0.050 0.050 scale +0 setgray +newpath +(Helvetica) findfont 240 scalefont setfont +1.000 UL +LTb +935 2772 M +63 0 V +2457 0 R +-63 0 V +stroke +791 2772 M +[ [(Helvetica) 240.0 0.0 true true 0 (0.00)] +] -80.0 MRshow +1.000 UL +LTb +935 3066 M +63 0 V +2457 0 R +-63 0 V +stroke +791 3066 M +[ [(Helvetica) 240.0 0.0 true true 0 (0.05)] +] -80.0 MRshow +1.000 UL +LTb +935 3360 M +63 0 V +2457 0 R +-63 0 V +stroke +791 3360 M +[ [(Helvetica) 240.0 0.0 true true 0 (0.10)] +] -80.0 MRshow +1.000 UL +LTb +935 3654 M +63 0 V +2457 0 R +-63 0 V +stroke +791 3654 M +[ [(Helvetica) 240.0 0.0 true true 0 (0.15)] +] -80.0 MRshow +1.000 UL +LTb +935 3947 M +63 0 V +2457 0 R +-63 0 V +stroke +791 3947 M +[ [(Helvetica) 240.0 0.0 true true 0 (0.20)] +] -80.0 MRshow +1.000 UL +LTb +935 4241 M +63 0 V +2457 0 R +-63 0 V +stroke +791 4241 M +[ [(Helvetica) 240.0 0.0 true true 0 (0.25)] +] -80.0 MRshow +1.000 UL +LTb +935 4535 M +63 0 V +2457 0 R +-63 0 V +stroke +791 4535 M +[ [(Helvetica) 240.0 0.0 true true 0 (0.30)] +] -80.0 MRshow +1.000 UL +LTb +935 2772 M +0 63 V +0 1700 R +0 -63 V +1250 2772 M +0 63 V +0 1700 R +0 -63 V +1565 2772 M +0 63 V +0 1700 R +0 -63 V +1880 2772 M +0 63 V +0 1700 R +0 -63 V +2195 2772 M +0 63 V +0 1700 R +0 -63 V +2510 2772 M +0 63 V +0 1700 R +0 -63 V +2825 2772 M +0 63 V +0 1700 R +0 -63 V +3140 2772 M +0 63 V +0 1700 R +0 -63 V +3455 2772 M +0 63 V +0 1700 R +0 -63 V +stroke +935 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0.65 0.00 C 935 2942 M +315 6 V +315 -17 V +315 0 V +315 0 V +315 0 V +315 0 V +315 0 V +315 0 V +935 2942 Dia +1250 2948 Dia +1565 2931 Dia +1880 2931 Dia +2195 2931 Dia +2510 2931 Dia +2825 2931 Dia +3140 2931 Dia +3455 2931 Dia +% End plot #3 +% Begin plot #4 +2.000 UP +1.000 UL +LT3 +0.75 0.50 1.00 C 935 3442 M +315 -18 V +315 -29 V +315 -24 V +315 30 V +315 -30 V +315 -11 V +315 17 V +315 0 V +935 3442 DiaF +1250 3424 DiaF +1565 3395 DiaF +1880 3371 DiaF +2195 3401 DiaF +2510 3371 DiaF +2825 3360 DiaF +3140 3377 DiaF +3455 3377 DiaF +% End plot #4 +1.000 UL +LTb +935 4535 N +0 -1763 V +2520 0 V +0 1763 V +-2520 0 V +Z stroke +2.000 UP +1.000 UL +LTb +1.000 UL +LTb +3960 2772 M +63 0 V +2456 0 R +-63 0 V +3960 3066 M +63 0 V +2456 0 R +-63 0 V +3960 3360 M +63 0 V +2456 0 R +-63 0 V +3960 3654 M +63 0 V +2456 0 R +-63 0 V +3960 3947 M +63 0 V +2456 0 R +-63 0 V +3960 4241 M +63 0 V +2456 0 R +-63 0 V +3960 4535 M +63 0 V +2456 0 R +-63 0 V +3960 2772 M +0 63 V +0 1700 R +0 -63 V 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0.00 C 3960 2942 M +420 -11 V +420 0 V +420 0 V +419 0 V +420 0 V +420 0 V +3960 2942 Dia +4380 2931 Dia +4800 2931 Dia +5220 2931 Dia +5639 2931 Dia +6059 2931 Dia +6479 2931 Dia +% End plot #3 +% Begin plot #4 +2.000 UP +1.000 UL +LT3 +0.75 0.50 1.00 C 3960 3477 M +420 -64 V +420 -24 V +420 6 V +419 -623 V +420 617 V +420 -23 V +3960 3477 DiaF +4380 3413 DiaF +4800 3389 DiaF +5220 3395 DiaF +5639 2772 DiaF +6059 3389 DiaF +6479 3366 DiaF +% End plot #4 +1.000 UL +LTb +3960 4535 N +0 -1763 V +2519 0 V +0 1763 V +-2519 0 V +Z stroke +2.000 UP +1.000 UL +LTb +1.000 UL +LTb +935 655 M +63 0 V +2457 0 R +-63 0 V +stroke +791 655 M +[ [(Helvetica) 240.0 0.0 true true 0 ( 0.00)] +] -80.0 MRshow +1.000 UL +LTb +935 876 M +63 0 V +2457 0 R +-63 0 V +stroke +791 876 M +[ [(Helvetica) 240.0 0.0 true true 0 ( 0.10)] +] -80.0 MRshow +1.000 UL +LTb +935 1096 M +63 0 V +2457 0 R +-63 0 V +stroke +791 1096 M +[ [(Helvetica) 240.0 0.0 true true 0 ( 0.20)] +] -80.0 MRshow +1.000 UL +LTb +935 1317 M +63 0 V +2457 0 R +-63 0 V +stroke +791 1317 M +[ [(Helvetica) 240.0 0.0 true true 0 ( 0.30)] +] -80.0 MRshow +1.000 UL +LTb +935 1537 M +63 0 V +2457 0 R +-63 0 V +stroke +791 1537 M +[ [(Helvetica) 240.0 0.0 true true 0 ( 0.40)] +] -80.0 MRshow +1.000 UL +LTb +935 1758 M +63 0 V +2457 0 R +-63 0 V +stroke +791 1758 M +[ [(Helvetica) 240.0 0.0 true true 0 ( 0.50)] +] -80.0 MRshow +1.000 UL +LTb +935 1978 M +63 0 V +2457 0 R +-63 0 V +stroke +791 1978 M +[ [(Helvetica) 240.0 0.0 true true 0 ( 0.60)] +] -80.0 MRshow +1.000 UL +LTb +935 2199 M +63 0 V +2457 0 R +-63 0 V +stroke +791 2199 M +[ [(Helvetica) 240.0 0.0 true true 0 ( 0.70)] +] -80.0 MRshow +1.000 UL +LTb +935 2419 M +63 0 V +2457 0 R +-63 0 V +stroke +791 2419 M +[ [(Helvetica) 240.0 0.0 true true 0 ( 0.80)] +] -80.0 MRshow +1.000 UL +LTb +935 655 M +0 63 V +0 1701 R +0 -63 V +stroke +935 415 M +[ [(Helvetica) 240.0 0.0 true true 0 ( 0)] +] -80.0 MCshow +1.000 UL +LTb +1250 655 M +0 63 V +0 1701 R +0 -63 V +stroke +1250 415 M 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Dia +6479 1993 Dia +% End plot #3 +% Begin plot #4 +2.000 UP +1.000 UL +LT3 +0.75 0.50 1.00 C 3960 1470 M +420 135 V +420 -5 V +420 24 V +5639 655 L +420 1021 V +420 -15 V +3960 1470 DiaF +4380 1605 DiaF +4800 1600 DiaF +5220 1624 DiaF +5639 655 DiaF +6059 1676 DiaF +6479 1661 DiaF +% End plot #4 +1.000 UL +LTb +3960 2419 N +0 -1764 V +2519 0 V +0 1764 V +-2519 0 V +Z stroke +2.000 UP +1.000 UL +LTb +stroke +grestore +end +showpage +%%Trailer +%%DocumentFonts: Helvetica diff --git a/papers/2011_emnlp_unsup_impact/figures/dv-rel-results.p b/papers/2011_emnlp_unsup_impact/figures/dv-rel-results.p new file mode 100644 index 00000000..50337611 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/dv-rel-results.p @@ -0,0 +1,85 @@ +set term postscript eps enhanced color lw 3 "Helvetica" 24 +set output 'dv-rel-results.eps' +#set terminal png transparent nocrop enhanced font arial 8 size 500,350 +#set output 'dv-rel-results.png' + +set pointsize 2 +set multiplot +set size 0.35,0.35 + +# FIXME: the key needs to go at the bottom of all the plots +unset key +#set key outside bottom center vertical noreverse enhanced autotitles nobox + +set xtics mirror +set format x "%2.0f" +set format y "%.2f" + +set yrange [ 0.0 : 0.30 ] noreverse nowriteback +set ylabel "V-Measure" +set format x '' +set title "ukWaC" + +set lmargin 0 +set rmargin 0 +set bmargin 0 +set tmargin 0 +set origin 0.13, 0.55 + +# UKWAC data +plot 'dv-wordsi-rel-scores-ukwac.dat' using 1:3 title "K-Means V-Measure" ls 2 pt 3 lw 1 lc rgb "red" lt 1 axis x1y1 with linespoints, \ + 'dv-wordsi-rel-scores-ukwac.dat' using 1:5 title "Spectra V-Measure" ls 2 pt 11 lw 1 lc rgb "green" lt 2 axis x1y1 with linespoints, \ + 'dv-wordsi-rel-scores-ukwac.dat' using 1:7 title "CBC V-Measure" ls 2 pt 12 lw 1 lc rgb "orange" lt 3 axis x1y1 with linespoints, \ + 'dv-wordsi-rel-scores-ukwac.dat' using 1:9 title "On-line K-Means V-Measure" ls 2 pt 13 lw 1 lc rgb "purple" lt 4 axis x1y1 with linespoints + +unset ylabel +set format y '' +set title "Wikipedia" +set origin 0.55, 0.55 + +# WIKIPEDIA +plot 'dv-wordsi-rel-scores-wiki.dat' using 1:3 title "K-Means V-Measure" ls 2 pt 3 lw 1 lc rgb "red" lt 1 axis x1y1 with linespoints, \ + 'dv-wordsi-rel-scores-wiki.dat' using 1:5 title "Spectra V-Measure" ls 2 pt 11 lw 1 lc rgb "green" lt 2 axis x1y1 with linespoints, \ + 'dv-wordsi-rel-scores-wiki.dat' using 1:7 title "CBC V-Measure" ls 2 pt 12 lw 1 lc rgb "orange" lt 3 axis x1y1 with linespoints, \ + 'dv-wordsi-rel-scores-wiki.dat' using 1:9 title "On-line K-Means V-Measure" ls 2 pt 13 lw 1 lc rgb "purple" lt 4 axis x1y1 with linespoints + +# remove the ukWaC and Wikipedia titles for the lower graphs +unset title +# add the xtic labeling back +set format x ' %g' +set format y ' %.2f' + +set xtics auto +set ylabel "Paired FScore" +set xlabel 'Segment Number' +# NOTE: this range should stay fixed across all result plots +# to ensure horizontal readability +set yrange [ 0.0 : 0.80 ] noreverse nowriteback + + +#set xrange [ 1 : 8 ] noreverse nowriteback +set ytics auto + +set origin 0.13, 0.13 + +# UKWAC +plot 'dv-wordsi-rel-scores-ukwac.dat' using 1:2 title "K-Means F-Score" ls 1 pt 3 lw 1 lc rgb "red" lt 1 axis x1y1 with linespoints, \ + 'dv-wordsi-rel-scores-ukwac.dat' using 1:4 title "Spectral F-Score" ls 1 pt 11 lw 1 lc rgb "green" lt 2 axis x1y1 with linespoints, \ + 'dv-wordsi-rel-scores-ukwac.dat' using 1:6 title "CBC F-Score" ls 1 pt 12 lw 1 lc rgb "orange" lt 3 axis x1y1 with linespoints, \ + 'dv-wordsi-rel-scores-ukwac.dat' using 1:8 title "On-line K-Means F-Score" ls 1 pt 13 lw 1 lc rgb "purple" lt 4 axis x1y1 with linespoints + +unset ylabel +set format y '' +set origin 0.55, 0.13 + +# WIKIPEDIA +plot 'dv-wordsi-rel-scores-wiki.dat' using 1:2 title "K-Means F-Score" ls 1 pt 3 lw 1 lc rgb "red" lt 1 axis x1y1 with linespoints, \ + 'dv-wordsi-rel-scores-wiki.dat' using 1:4 title "Spectral F-Score" ls 1 pt 11 lw 1 lc rgb "green" lt 2 axis x1y1 with linespoints, \ + 'dv-wordsi-rel-scores-wiki.dat' using 1:6 title "CBC F-Score" ls 1 pt 12 lw 1 lc rgb "orange" lt 3 axis x1y1 with linespoints, \ + 'dv-wordsi-rel-scores-wiki.dat' using 1:8 title "On-line K-Means F-Score" ls 1 pt 13 lw 1 lc rgb "purple" lt 4 axis x1y1 with linespoints + + + + + + diff --git a/papers/2011_emnlp_unsup_impact/figures/dv-wc-wordsi-25-cbc.dat b/papers/2011_emnlp_unsup_impact/figures/dv-wc-wordsi-25-cbc.dat new file mode 100644 index 00000000..74054873 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/dv-wc-wordsi-25-cbc.dat @@ -0,0 +1,2611 @@ +# term1 term2 pos simScore psdScore +file layer NOUN 0.09665135369020475 0.886154 0.001311 +facilities grades NOUN 0.1050413854029532 0.892330 0.002454 +fleet house NOUN 0.09327143017196153 0.872847 0.000553 +facility homes NOUN 0.23300229084117977 0.861320 0.005933 +electricity manufacturers NOUN 0.14954562094522098 0.862826 0.003217 +election lack NOUN 0.12408058803891991 0.835286 0.001208 +files particles NOUN 0.10604277916212264 0.909155 0.002411 +explanation permission NOUN 0.3438017337599127 0.901921 0.002522 +engineer manufacturers NOUN 0.11811815491009549 0.886398 0.001666 +features others NOUN 0.13649688302201224 0.919382 0.001168 +file input NOUN 0.14431291368394544 0.909127 0.003867 +element layer NOUN 0.10740852239163833 0.898779 0.001275 +focus inspiration NOUN 0.1584991959210019 0.794348 0.007326 +festival meetings NOUN 0.40955785071176026 0.865138 0.001675 +firm offices NOUN 0.14505299050470744 0.915115 0.002567 +enemies experience NOUN 0.2518864764918647 0.882282 0.004094 +employment information NOUN 0.27804458785948566 0.921722 0.000488 +energy memory NOUN 0.1713719230516431 0.827141 0.008289 +eye infrastructure NOUN 0.16822953108338223 0.879067 0.000939 +extension format NOUN 0.24131374338950523 0.857071 0.001299 +focus location NOUN 0.2350800006639828 0.757260 0.004821 +explanation origin NOUN 0.19042621306180516 0.791010 0.001137 +forces guest NOUN 0.08624223989529328 0.781676 0.022131 +end limit NOUN 0.10958427885659856 0.756984 0.000171 +extent numbers NOUN 0.0879468139220409 0.819786 0.001413 +food items NOUN 0.19981483900862682 0.661625 0.039598 +flag forces NOUN 0.15886938864515052 0.762372 0.018190 +fire parks NOUN 0.16000706293920924 0.879592 0.001781 +films list NOUN 0.15963729577063368 0.901565 0.001805 +elements others NOUN 0.1396436613111732 0.858646 0.001036 +figures musicians NOUN 0.19831541999263955 0.806497 0.025371 +element features NOUN 0.27558060994891687 0.856326 0.005559 +employment honors NOUN 0.12570141167660825 0.914807 0.001019 +facilities homes NOUN 0.23061908204734222 0.899149 0.001208 +electricity model NOUN 0.1805896253512857 0.887601 0.000209 +facility farm NOUN 0.19739997456915814 0.757206 0.017171 +end farm NOUN 0.21722183648097212 0.894547 0.002823 +face foot NOUN 0.12221464224310036 0.864711 0.001195 +employees office NOUN 0.09453872557842892 0.878342 0.000427 +enemy model NOUN 0.1448329774580015 0.828343 0.001301 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0.850390 0.001759 +face person NOUN 0.17473395393985852 0.873660 0.003206 +fish participants NOUN 0.18960041145016146 0.827117 0.000524 +explanation orders NOUN 0.1665313778517571 0.895618 0.002164 +elements images NOUN 0.3243490527199895 0.889579 0.001199 +fleet planet NOUN 0.1642683544885559 0.868142 0.002213 +field operations NOUN 0.12575762057727077 0.826457 0.001949 +followers inhabitants NOUN 0.2832994499861355 0.701602 0.028791 +features mechanism NOUN 0.2209149928368876 0.934863 0.000945 +films ones NOUN 0.20284202189156053 0.757345 0.006912 +face instance NOUN 0.14804987292918373 0.805208 0.024016 +extension guns NOUN 0.06654941442180015 0.892682 0.002881 +fight movement NOUN 0.20085830802519788 0.838542 0.003571 +firm officials NOUN 0.1791259584529727 0.934041 0.003170 +facilities faculty NOUN 0.12794634268228894 0.928993 0.000960 +elements limits NOUN 0.17295777861061143 0.837575 0.000891 +festival music NOUN 0.2399925599836181 0.823064 0.005908 +fishing operations NOUN 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0.14674511245781166 0.819592 0.026247 +floor ground NOUN 0.16892125742478056 0.736652 0.016804 +exposure pain NOUN 0.20123516554808615 0.581873 0.026846 +energy increase NOUN 0.1534252611376862 0.834619 0.001765 +emperor moment NOUN 0.10336098627921302 0.899058 0.001219 +feet pages NOUN 0.23768640815653497 0.824855 0.002283 +elements physics NOUN 0.08629874995375143 0.879435 0.000541 +firm foundation NOUN 0.12008727803435408 0.890057 0.001969 +face half NOUN 0.10281033134858725 0.794992 0.000589 +facility harbor NOUN 0.029430353844228513 0.907645 0.002388 +element option NOUN 0.1879486288306605 0.845322 0.000575 +employees municipality NOUN 0.193261872749831 0.910720 0.000240 +energy oxygen NOUN 0.2502036525946724 0.812613 0.001972 +element feature NOUN 0.3050948543804169 0.886874 0.001121 +features ones NOUN 0.27067916268425896 0.891385 0.001029 +elections merger NOUN 0.150943450370973 0.844691 0.000175 +face maximum NOUN 0.17185553529148911 0.821797 0.001308 +facilities missile NOUN 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0.08267602738618768 0.509419 0.000638 +equipment operations NOUN 0.3592387930430725 0.499499 0.000076 +elements phase NOUN 0.1673639833083187 0.539810 0.000063 +employees funds NOUN 0.21916607266258376 0.529695 0.000461 +entertainment insurance NOUN 0.16695519042067547 0.503515 0.000211 +faculty physics NOUN 0.08945523049526335 0.471549 0.000640 +elements nations NOUN 0.16196770972289998 0.546283 0.000119 +fleet palace NOUN 0.11515699622149247 0.550606 0.004728 +emphasis guest NOUN 0.06781076646296263 0.702006 0.000309 +episode leg NOUN 0.18969606562424463 0.556930 0.000514 +flag involvement NOUN 0.14160222665245084 0.535811 0.000191 +era form NOUN 0.2160294060836045 0.599158 0.000064 +episodes movie NOUN 0.2510517804011711 0.549464 0.001459 +employees enemies NOUN 0.2259714643672611 0.510672 0.000095 +equipment experiments NOUN 0.22633220503871515 0.524086 0.000070 +engineer official NOUN 0.12897065289432122 0.579928 0.000431 +flag level NOUN 0.13329874961071783 0.502508 0.000727 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0.11201691574725256 0.586466 0.005679 +flights launch NOUN 0.1431173502350022 0.552966 0.003422 +enemy library NOUN 0.21460219181416892 0.540603 0.000411 +elements memory NOUN 0.18644282387306074 0.502254 0.001329 +entrance lake NOUN 0.13378401285024066 0.528670 0.000050 +element note NOUN 0.18871158098077984 0.548481 0.000787 +energy index NOUN 0.11629951031781624 0.521294 0.000869 +employees parent NOUN 0.1786730462777131 0.590607 0.000909 +entertainment folk NOUN 0.18684821309009514 0.518975 0.000469 +electricity employment NOUN 0.14840786749495666 0.502050 0.000439 +entry maximum NOUN 0.11706338639639698 0.589939 0.001698 +episode issue NOUN 0.24681373041756485 0.531770 0.000196 +fish markets NOUN 0.13013669895703164 0.573716 0.001040 +environment oil NOUN 0.13733258823623185 0.522422 0.002882 +farmers newspaper NOUN 0.30215700930258166 0.516113 0.005096 +era office NOUN 0.10004090001781937 0.534602 0.001457 +entry extension NOUN 0.14522432545451894 0.542668 0.001619 +explanation job NOUN 0.16136745570857702 0.574506 0.003124 +favor god NOUN 0.10621911913100793 0.541082 0.004118 +elements places NOUN 0.31569641129497567 0.541516 0.000345 +enemy guns NOUN 0.09463109926383746 0.537807 0.001385 +equipment networks NOUN 0.2541192759519827 0.505357 0.000071 +experiment missions NOUN 0.17489163025973614 0.552597 0.001948 +fame law NOUN 0.023812729040249357 0.529854 0.001273 +experiment incident NOUN 0.17146433862429372 0.504405 0.006917 +fact pair NOUN 0.09167418933403308 0.577255 0.014357 +emperor followers NOUN 0.09904448253925419 0.576796 0.002082 +engineer historian NOUN 0.1914073666179831 0.561134 0.001372 +element object NOUN 0.2262317827636071 0.521905 0.000358 +faculty medicine NOUN 0.16983063208940918 0.521326 0.001588 +employees facilities NOUN 0.22073195972022694 0.509062 0.000125 +engineer facility NOUN 0.12466684762656217 0.537237 0.000432 +elements feature NOUN 0.2737048601295641 0.564529 0.000199 +experiment phenomenon NOUN 0.17813287849899384 0.497797 0.003398 +faith identity NOUN 0.16022949401662143 0.566841 0.009224 +father friend NOUN 0.12423596652527442 0.590968 0.010340 +experiment information NOUN 0.17947560940575155 0.582583 0.005312 +entertainment movies NOUN 0.253889828870985 0.510775 0.000321 +elements list NOUN 0.1478787937583711 0.557305 0.002225 +employees fire NOUN 0.1330597959702655 0.511863 0.000056 +faith minority NOUN 0.12835339125808962 0.579274 0.003475 +end leg NOUN 0.12418326087253055 0.643015 0.005619 +floor home NOUN 0.1077656282745917 0.562262 0.003569 +energy physics NOUN 0.11661289885393565 0.527149 0.001061 +end location NOUN 0.14485040821332157 0.583625 0.002835 +floor grade NOUN 0.10561525249105619 0.490441 0.013024 +episodes periods NOUN 0.1350407520321207 0.568551 0.000150 +environment homes NOUN 0.18252471452554972 0.519231 0.000905 +fall incident NOUN 0.12528564063041409 0.559319 0.001842 +fashion patterns NOUN 0.2711382610416266 0.617388 0.005664 +flights hours NOUN 0.11672123211610516 0.562581 0.001312 +election merger NOUN 0.12924724632121334 0.564308 0.000970 +elections festival NOUN 0.2863457231874849 0.564978 0.000267 +flag league NOUN 0.07967370756306491 0.546174 0.009239 +employees governments NOUN 0.19658652640711355 0.530862 0.000610 +faith person NOUN 0.13338106081047058 0.532190 0.002332 +fans patients NOUN 0.23001422975088595 0.569469 0.003461 +employment expansion NOUN 0.15951184934852602 0.532739 0.000366 +fans fiction NOUN 0.08261851758382963 0.573460 0.006459 +experience philosophy NOUN 0.1741427813049605 0.540936 0.001681 +end parts NOUN 0.22183831343372276 0.565992 0.000866 +engineer guitarist NOUN 0.11101567089062382 0.580012 0.000382 +elements metal NOUN 0.1675526672924128 0.509167 0.000272 +entry image NOUN 0.15230401360669155 0.526358 0.000995 +engines items NOUN 0.12979364522487277 0.508308 0.000427 +faculty members NOUN 0.14680025580974523 0.526358 0.003639 +employment experience NOUN 0.19334037094480092 0.522636 0.000339 +experiment patterns NOUN 0.22937814459636052 0.536490 0.003005 +engineer manufacturers NOUN 0.11811815491009549 0.549094 0.000273 +favor household NOUN 0.10604820384746391 0.629530 0.011032 +fans passengers NOUN 0.1299080529212221 0.508856 0.002675 +elements organizations NOUN 0.22235731043931542 0.541090 0.001076 +era peace NOUN 0.11777428342610541 0.589279 0.000953 +entry expansion NOUN 0.18100505581045456 0.526253 0.000740 +fishing meat NOUN 0.09182855875006618 0.542977 0.004066 +episodes percent NOUN 0.25069606499299474 0.531438 0.000143 +fans places NOUN 0.18645104006283228 0.588837 0.006723 +father none NOUN 0.027328362822044146 0.621083 0.024043 +enemy heart NOUN 0.14622445734144296 0.534995 0.000019 +elements origins NOUN 0.2594467520334965 0.518897 0.000168 +equipment graphics NOUN 0.15164024297362352 0.502113 0.000424 +environment form NOUN 0.23263582944084668 0.567692 0.000122 +end junction NOUN 0.2360801387116204 0.566419 0.001739 +election idea NOUN 0.11775644452311852 0.534676 0.000268 +elements era NOUN 0.1668515019020081 0.535371 0.002698 +# term1 term2 pos simScore psdScore diff --git a/papers/2011_emnlp_unsup_impact/figures/dv-wc-wordsi-order-scores-psd.dat b/papers/2011_emnlp_unsup_impact/figures/dv-wc-wordsi-order-scores-psd.dat new file mode 100644 index 00000000..7d97de5b --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/dv-wc-wordsi-order-scores-psd.dat @@ -0,0 +1,3 @@ +# segment k-means-f k-means-v spec-f spec-v cbc-f cbc-v online-f online-v +0 0.0 0.0 0.0 0.792888172049 0.135158135901 +1 0.0 0.0 0.0 0.0 diff --git a/papers/2011_emnlp_unsup_impact/figures/dv-wc-wordsi-order-scores-ukwac.dat b/papers/2011_emnlp_unsup_impact/figures/dv-wc-wordsi-order-scores-ukwac.dat new file mode 100644 index 00000000..fbf9e6c0 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/dv-wc-wordsi-order-scores-ukwac.dat @@ -0,0 +1,10 @@ +# segment k-means-f k-means-v spec-f spec-v cbc-f cbc-v online-f online-v +0 0.0 0.0 0.3341235648915307 0.126 0.05447024237792709 0.292 0.3506989243044264 0.128 +1 0.0 0.0 0.3556355498620261 0.121 0.05474561146191701 0.291 0.4050859742978117 0.123 +2 0.0 0.0 0.35085959064124883 0.127 0.05511596203050272 0.293 0.43949049102510024 0.121 +3 0.0 0.0 0.35563565327260765 0.121 0.056689761162537614 0.292 0.4397796895790214 0.115 +4 0.0 0.0 0.3599039240383986 0.118 0.05617020344917284 0.292 0.4534757375220293 0.117 +5 0.0 0.0 0.3788513303143586 0.119 0.053488138060633066 0.291 0.44664571736024705 0.106 +6 0.0 0.0 0.3605278439860727 0.116 0.11507153539264685 0.277 0.4575482363514336 0.109 +7 0.0 0.0 0.36536941549323104 0.113 0.11560391057296564 0.277 0.42624108509133607 0.115 +8 0.0 0.0 0.37814075300430916 0.117 0.11293494976359741 0.276 0.41448658559055057 0.12 diff --git a/papers/2011_emnlp_unsup_impact/figures/dv-wc-wordsi-order-scores-wiki.dat b/papers/2011_emnlp_unsup_impact/figures/dv-wc-wordsi-order-scores-wiki.dat new file mode 100644 index 00000000..a57a35c7 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/dv-wc-wordsi-order-scores-wiki.dat @@ -0,0 +1,8 @@ +# segment k-means-f k-means-v spec-f spec-v cbc-f cbc-v online-f online-v +0 0.0 0.0 0.3396160497295356 0.126 0.052336957873767014 0.291 0.35186534608860826 0.136 +1 0.0 0.0 0.34866683909690516 0.126 0.05292552480214448 0.29 0.4049355631276 0.119 +2 0.0 0.0 0.35758825460933524 0.129 0.05154701787136734 0.293 0.42868928969842646 0.123 +3 0.0 0.0 0.34607586200081386 0.12 0.052980652513274905 0.293 0.4352392905685533 0.116 +4 0.0 0.0 0.3652853888338275 0.118 0.05399104039868371 0.295 0.4348690930211146 0.127 +5 0.0 0.0 0.3818834728998791 0.118 0.05181302004105827 0.293 0.4273392724149799 0.12 +6 0.0 0.0 0.38006315093528686 0.131 0.05243832541005984 0.294 0.42908898394780925 0.105 diff --git a/papers/2011_emnlp_unsup_impact/figures/dv-wc-wordsi-order-stkm.dat b/papers/2011_emnlp_unsup_impact/figures/dv-wc-wordsi-order-stkm.dat new file mode 100644 index 00000000..a767a87b --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/dv-wc-wordsi-order-stkm.dat @@ -0,0 +1,4977 @@ +# term1 term2 pos simScore psdScore +empire journalist NOUN 0.1674908741062871 0.774294 0.001420 +form implementation NOUN 0.2790211481567622 0.851117 0.001167 +followers places NOUN 0.2531309063140091 0.829843 0.002812 +extension maintenance NOUN 0.1556574090782601 0.871084 0.001090 +facility municipality NOUN 0.11886795238546029 0.904624 0.003855 +elements physics NOUN 0.08629874995375143 0.634797 0.001036 +elements movements NOUN 0.285539826784524 0.577956 0.000238 +facilities girls NOUN 0.10945651827054301 0.790169 0.000836 +facilities library NOUN 0.22155357467457143 0.846716 0.005494 +exposure network NOUN 0.1887668892646738 0.792610 0.000672 +facility papers NOUN 0.1742452973367002 0.757033 0.003722 +elements jazz NOUN 0.16651618596463924 0.644569 0.000657 +followers heart NOUN 0.05336179057405993 0.836737 0.011010 +election laws NOUN 0.11725187069415596 0.590463 0.000370 +elements fans NOUN 0.1970242693583914 0.581489 0.000048 +extension harbor NOUN 0.030796848380403946 0.858729 0.003238 +form ones NOUN 0.29032298937850537 0.870428 0.001743 +forest palace NOUN 0.1084634382827927 0.880308 0.004445 +format manner NOUN 0.2563418795917451 0.944673 0.000530 +element orbit NOUN 0.09281926134157507 0.650275 0.000860 +extent height NOUN 0.11279104082778947 0.945429 0.000412 +extension heritage NOUN 0.10136104352361135 0.808628 0.004932 +elements pair NOUN 0.21294212330858336 0.670776 0.003727 +extension path NOUN 0.16970310922134405 0.828611 0.004015 +elections governments NOUN 0.35172332669746303 0.620341 0.000088 +face fear NOUN 0.13396417676706082 0.798998 0.006140 +format methods NOUN 0.24195448949558704 0.767898 0.005380 +elements influences NOUN 0.39877589324618257 0.603392 0.000872 +elections newspaper NOUN 0.17439810274448328 0.647648 0.000174 +emphasis numbers NOUN 0.14693902315096335 0.794044 0.000144 +form logic NOUN 0.15635282733080755 0.866179 0.001167 +facilities fishing NOUN 0.1666409870320078 0.811931 0.006465 +food mixture NOUN 0.18824308981084528 0.938632 0.000406 +elements movies NOUN 0.1580213740640297 0.594524 0.000332 +face foot NOUN 0.12221464224310036 0.816543 0.001698 +followers minutes NOUN 0.12313804380583247 0.798459 0.001848 +emphasis equipment NOUN 0.15237477015061437 0.799519 0.000059 +empire influences NOUN 0.08860677215760719 0.671426 0.000574 +explanation models NOUN 0.20454548079298257 0.640761 0.000487 +form music NOUN 0.24849432984419292 0.881091 0.001305 +elements movement NOUN 0.19028159133368325 0.605511 0.000040 +electricity equipment NOUN 0.18370524277440378 0.572454 0.000551 +facility force NOUN 0.13183452148280855 0.771912 0.006445 +format object NOUN 0.21928420902117243 0.804749 0.003546 +followers mother NOUN 0.2029269836568256 0.882671 0.001356 +emphasis features NOUN 0.17464429743527998 0.774757 0.000328 +facilities medium NOUN 0.17254698935054397 0.813138 0.004078 +form letter NOUN 0.15831082722144763 0.848546 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NOUN 0.24683896930934232 0.612002 0.000116 +folk hall NOUN 0.14308417677523555 0.697115 0.001131 +element planet NOUN 0.13000560999113092 0.698497 0.002698 +elements ideas NOUN 0.4421058853668334 0.560321 0.000300 +empire influence NOUN 0.13875486324625483 0.648562 0.000623 +elections nomination NOUN 0.17094787447093726 0.672975 0.000447 +face god NOUN 0.16883893720410306 0.863941 0.001538 +elements index NOUN 0.09835958265770244 0.599396 0.001315 +face pitch NOUN 0.14170538967334556 0.828809 0.000751 +extension half NOUN 0.21539018905963084 0.921113 0.001071 +facilities materials NOUN 0.18780131065788871 0.762396 0.000321 +folk legend NOUN 0.15149960056576367 0.681258 0.000146 +form noise NOUN 0.15388697111063865 0.862826 0.005229 +empire nation NOUN 0.1013999500891435 0.604330 0.001624 +followers kingdom NOUN 0.21828815867192636 0.897777 0.003097 +emphasis form NOUN 0.14630093123629634 0.827669 0.000115 +food parent NOUN 0.08334303554451343 0.797462 0.004075 +elements medium NOUN 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needs NOUN 0.15915429650836602 0.612574 0.009889 +fan places NOUN 0.08436743329859062 0.633146 0.003488 +farmers money NOUN 0.14004553694478142 0.547283 0.001633 +employees members NOUN 0.34477036014459506 0.501102 0.000210 +fishing merchant NOUN 0.09178897541084827 0.522261 0.029070 +followers opponents NOUN 0.205906638853446 0.587246 0.004061 +followers members NOUN 0.32225246693611653 0.502455 0.005467 +factor moment NOUN 0.11874790104570324 0.488880 0.003640 +entertainment performances NOUN 0.15369896146166745 0.516181 0.000100 +focus influences NOUN 0.31181996047555205 0.592399 0.004286 +flights journey NOUN 0.14095788579644192 0.591810 0.004074 +flights force NOUN 0.08584447361790047 0.573045 0.003692 +elements needs NOUN 0.1562950600841865 0.521034 0.000039 +era experience NOUN 0.1456543803660582 0.566032 0.000092 +fleet planet NOUN 0.1642683544885559 0.483180 0.005811 +entry implementation NOUN 0.13927945794691024 0.521739 0.000225 +fan music NOUN 0.08606724115627208 0.481307 0.001990 +farmers food NOUN 0.16608169665681607 0.612335 0.005563 +error maximum NOUN 0.1306215085705911 0.530054 0.000535 +farm municipality NOUN 0.1314375604037375 0.550430 0.001748 +format medium NOUN 0.1660247975272882 0.493092 0.001377 +fire homes NOUN 0.1426135714494438 0.573345 0.014095 +equation logic NOUN 0.0913103786334064 0.489693 0.000138 +environment maintenance NOUN 0.16324200554983972 0.523180 0.000329 +employees officers NOUN 0.17096581597744698 0.503905 0.000062 +father marriage NOUN 0.1414443414340749 0.525741 0.003827 +fire motor NOUN 0.12468122127934553 0.541141 0.003451 +engines features NOUN 0.14023380980398975 0.523452 0.000295 +fashion names NOUN 0.17947608068492163 0.517248 0.006170 +equation patient NOUN 0.08626194443060291 0.525988 0.000364 +forces missile NOUN 0.11869750775616646 0.519319 0.008533 +entertainment media NOUN 0.23078407967006936 0.524835 0.000028 +flights pilot NOUN 0.16206624037293382 0.606006 0.018351 +electricity increase NOUN 0.14285176226140597 0.525387 0.002875 +focus impact NOUN 0.15691121292929916 0.523180 0.006301 +films periods NOUN 0.16858928309742896 0.529341 0.006887 +environment forests NOUN 0.12531531628875597 0.520485 0.000251 +form note NOUN 0.2746525548289208 0.559868 0.001265 +forces guest NOUN 0.08624223989529328 0.634824 0.009129 +farm model NOUN 0.1533349982190086 0.546246 0.004472 +equipment industry NOUN 0.24424299810083341 0.517266 0.000231 +election fight NOUN 0.10922075994193803 0.506110 0.000047 +farm planet NOUN 0.14666970111195363 0.554710 0.012919 +episodes images NOUN 0.24005889190230562 0.517832 0.000191 +fashion logo NOUN 0.18208068438560615 0.631811 0.008156 +firm management NOUN 0.15577212988498876 0.560192 0.010007 +followers participants NOUN 0.4035478089257416 0.604276 0.002488 +environment industries NOUN 0.20165907338041092 0.505957 0.000174 +foot mouth NOUN 0.1255479055801575 0.604465 0.011168 +elements heritage NOUN 0.10279095706128176 0.517079 0.000151 +failure month NOUN 0.11376634060326944 0.576665 0.007422 +equation maps NOUN 0.10902749075544439 0.550315 0.002817 +elements historians NOUN 0.16973125887729995 0.537043 0.001357 +employment funding NOUN 0.34356941061216256 0.519263 0.000042 +elements orbit NOUN 0.15555164135673497 0.547221 0.000584 +films legs NOUN 0.1548437946097511 0.581353 0.007850 +era ideas NOUN 0.17478401359797685 0.550381 0.000842 +equipment mode NOUN 0.21788769323379445 0.552853 0.000149 +employees homes NOUN 0.21072499977289277 0.508712 0.000210 +firm maintenance NOUN 0.12739783636744026 0.579922 0.009358 +element ones NOUN 0.22316249297789403 0.539279 0.000734 +flights planes NOUN 0.11381494505610898 0.575382 0.004499 +farmers newspaper NOUN 0.30215700930258166 0.525320 0.005394 +entry exposure NOUN 0.139678610839971 0.505359 0.000175 +format genre NOUN 0.21144678004014383 0.568753 0.009683 +flag network NOUN 0.14084532021940616 0.537429 0.004490 +employees help NOUN 0.16902373449643235 0.513327 0.000141 +fish industries NOUN 0.14949959563746315 0.514609 0.010873 +electricity information NOUN 0.1795555588889373 0.501743 0.000287 +folk mainstream NOUN 0.3188062556483035 0.521687 0.008104 +forces movement NOUN 0.16101760196823448 0.583817 0.005843 +electricity flow NOUN 0.21381123176428066 0.510822 0.000769 +food funding NOUN 0.17970260702175136 0.607969 0.004090 +followers movements NOUN 0.20832672019348436 0.512266 0.002528 +emperor minute NOUN 0.12378858888386281 0.535840 0.001274 +enemies movements NOUN 0.30534421224576397 0.509472 0.000111 +fleet island NOUN 0.22970669959001058 0.587847 0.008207 +equipment format NOUN 0.23920115665269664 0.526231 0.000074 +elements origin NOUN 0.25199413208296323 0.517857 0.000240 +faculty firm NOUN 0.2602619175804997 0.590709 0.008946 +faith job NOUN 0.15387374331964349 0.584160 0.012644 +entertainment insurance NOUN 0.16695519042067547 0.532465 0.000685 +energy facilities NOUN 0.16199562817659738 0.527491 0.000076 +era office NOUN 0.10004090001781937 0.526390 0.000819 +employment implementation NOUN 0.2386670246865022 0.525325 0.000798 +entry introduction NOUN 0.13954108970157436 0.498998 0.000723 +entrance mouth NOUN 0.22276771393289369 0.528275 0.000462 +elements moment NOUN 0.1201436756132075 0.530768 0.000186 +engines option NOUN 0.1445331741468317 0.519664 0.000320 +farm land NOUN 0.06050835334604165 0.560497 0.008389 +forest harbor NOUN 0.033996794302180965 0.488889 0.000260 +folk historian NOUN 0.1425581395068424 0.555233 0.008200 +environment models NOUN 0.241366213285572 0.510811 0.000134 +floor hill NOUN 0.1104891691551416 0.525125 0.007013 +form noise NOUN 0.15388697111063865 0.591583 0.005234 +fame music NOUN 0.14521693600911695 0.518240 0.002677 +equipment networks NOUN 0.2541192759519827 0.500651 0.000437 +flights operators NOUN 0.11545172547419205 0.629227 0.005832 +engines images NOUN 0.1449702131063067 0.508558 0.000179 +father injury NOUN 0.12700970596087238 0.534448 0.003412 +enemy lines NOUN 0.15692017059077093 0.529595 0.000060 +forest passenger NOUN 0.2424784297805193 0.601462 0.006029 +father followers NOUN 0.1972331014844092 0.637629 0.014702 +elections festival NOUN 0.2863457231874849 0.528634 0.000107 +environment hotel NOUN 0.12606442724377817 0.536090 0.000174 +elements groups NOUN 0.3149837487527757 0.505610 0.000140 +force operations NOUN 0.25434163796509146 0.548743 0.002270 +forest park NOUN 0.4383656906778442 0.617741 0.014158 +favor judge NOUN 0.12254827714899254 0.532465 0.006027 +entry match NOUN 0.1448593179431422 0.531009 0.000308 +forests kingdom NOUN 0.09251648293876658 0.548177 0.005196 +fall introduction NOUN 0.12779379610346697 0.661588 0.000710 +employment honors NOUN 0.12570141167660825 0.481371 0.003105 +engineer musician NOUN 0.11957093310001987 0.515674 0.000044 +followers jobs NOUN 0.20396826368783105 0.567297 0.007579 +environment management NOUN 0.2636476699900396 0.510261 0.000047 +element ideas NOUN 0.20326722299532937 0.550401 0.000328 +elements followers NOUN 0.21610927703775687 0.555544 0.000341 +flights newspaper NOUN 0.1941001405084955 0.578689 0.011740 +environment flow NOUN 0.12640577835518482 0.507964 0.000237 +entertainment graphics NOUN 0.12701236902703772 0.527932 0.000757 +forest junction NOUN 0.17846193558823412 0.544243 0.004807 +followers membership NOUN 0.19054913570999824 0.554065 0.003842 +foot hour NOUN 0.10395598731673115 0.539401 0.003430 +foot mile NOUN 0.025808291236566045 0.544636 0.008559 +force missions NOUN 0.15160803845220525 0.536512 0.008406 +element letter NOUN 0.12997163361708652 0.559021 0.001687 +environment opponents NOUN 0.15549413903672746 0.519427 0.000364 +equipment personality NOUN 0.13145853794403203 0.515479 0.000121 +employees patients NOUN 0.2271424291971918 0.525878 0.000502 +elements focus NOUN 0.23358729229630257 0.540727 0.000091 +employment infrastructure NOUN 0.2136723849187945 0.506156 0.000005 +episodes issue NOUN 0.17233905788913828 0.534476 0.000358 +followers musicians NOUN 0.21321315769042515 0.536426 0.003136 +elements graphics NOUN 0.1049773088470907 0.544451 0.001446 +floor mixture NOUN 0.10238945461722684 0.697788 0.009032 +favor involvement NOUN 0.10201229463325209 0.562988 0.016090 +employment length NOUN 0.22747915456544554 0.537445 0.000184 +father mind NOUN 0.21246868842852953 0.546884 0.004425 +employees models NOUN 0.1954057866281818 0.515813 0.000041 +episode phase NOUN 0.2843957199926532 0.520877 0.000245 +forest hills NOUN 0.297514666635908 0.635062 0.008163 +father god NOUN 0.3182370907348626 0.516481 0.004547 +father job NOUN 0.20214111377408664 0.586438 0.004926 +fans inhabitants NOUN 0.19779725146415084 0.547648 0.008362 +forces housing NOUN 0.01967323809423818 0.685811 0.023543 +enemies historians NOUN 0.17211189687428144 0.520156 0.000074 +employees ministers NOUN 0.14708020821340498 0.533462 0.006598 +flights meetings NOUN 0.1188275491846177 0.544281 0.008486 +enemies existence NOUN 0.14880116378796773 0.536996 0.001404 +episode films NOUN 0.13433188733789114 0.556213 0.000292 +equipment gas NOUN 0.08998551786843123 0.534441 0.000188 +force links NOUN 0.07590788237076741 0.538932 0.006155 +error example NOUN 0.13832437632341388 0.505208 0.000068 +films motion NOUN 0.05956449950694212 0.632461 0.003889 +error material NOUN 0.14042149722998742 0.515230 0.000016 +element material NOUN 0.18366626909120085 0.514383 0.000220 +focus participants NOUN 0.19674884789331626 0.547484 0.005947 +elements novel NOUN 0.1873588730499334 0.560765 0.000812 +equation object NOUN 0.12764442594000017 0.502162 0.000145 +empire involvement NOUN 0.09749476986717312 0.534288 0.000173 +electricity generation NOUN 0.19544215820653488 0.510870 0.001012 +energy maximum NOUN 0.1789748647634415 0.526796 0.000085 +floor level NOUN 0.3741956521129916 0.607658 0.007596 +episodes match NOUN 0.1672617256053725 0.548232 0.000620 +enemy fire NOUN 0.14661134452343969 0.514168 0.000214 +father hands NOUN 0.16568796428821228 0.551949 0.005023 +forest ocean NOUN 0.07045555209102984 0.618428 0.009158 +# term1 term2 pos simScore psdScore diff --git a/papers/2011_emnlp_unsup_impact/figures/dv-wc-wordsi-pos-scores-psd.dat b/papers/2011_emnlp_unsup_impact/figures/dv-wc-wordsi-pos-scores-psd.dat new file mode 100644 index 00000000..d12b0b53 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/dv-wc-wordsi-pos-scores-psd.dat @@ -0,0 +1,3 @@ +# segment k-means-f k-means-v spec-f spec-v cbc-f cbc-v online-f online-v +0 0.0 0.0 0.0 0.763666415974 0.162927402837 +1 0.0 0.0 0.0 0.0 diff --git a/papers/2011_emnlp_unsup_impact/figures/dv-wc-wordsi-pos-scores-ukwac.dat b/papers/2011_emnlp_unsup_impact/figures/dv-wc-wordsi-pos-scores-ukwac.dat new file mode 100644 index 00000000..0298fd3d --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/dv-wc-wordsi-pos-scores-ukwac.dat @@ -0,0 +1,10 @@ +# segment k-means-f k-means-v spec-f spec-v cbc-f cbc-v online-f online-v +0 0.2431711213335851 0.153 0.3402844339588588 0.125 0.1036635691771505 0.251 0.48850971938630755 0.084 +1 0.23552449038098608 0.149 0.3380714960333629 0.126 0.10074649312991905 0.253 0.48387042706626837 0.092 +2 0.23699993948868212 0.15 0.3523217457096568 0.133 0.09680002590775717 0.252 0.47335829769663573 0.087 +3 0.23730979051492695 0.155 0.0 0.0 0.09824911331572249 0.251 0.5185606659428239 0.08 +4 0.235207730039108 0.153 0.35603072603199176 0.124 0.1103241722335474 0.246 0.5225150349249517 0.075 +5 0.23842653887580406 0.155 0.3606392897727896 0.126 0.09604694462737454 0.252 0.5139181266341651 0.065 +6 0.27958186341455393 0.151 0.36729069593378705 0.124 0.15175081885516908 0.24 0.5405424684142343 0.072 +7 0.27947173873733105 0.152 0.3443403363443902 0.122 0.1501427013295703 0.241 0.5569251475675331 0.065 +8 0.27441784698936744 0.149 0.3581453008851822 0.126 0.1519614654288678 0.244 0.5694125452679483 0.059 diff --git a/papers/2011_emnlp_unsup_impact/figures/dv-wc-wordsi-pos-scores-wiki.dat b/papers/2011_emnlp_unsup_impact/figures/dv-wc-wordsi-pos-scores-wiki.dat new file mode 100644 index 00000000..04800bae --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/dv-wc-wordsi-pos-scores-wiki.dat @@ -0,0 +1,8 @@ +# segment k-means-f k-means-v spec-f spec-v cbc-f cbc-v online-f online-v +0 0.24095882553280035 0.15 0.33615315539253193 0.127 0.10233679426802733 0.251 0.0 0.0 +1 0.23602802223253083 0.151 0.355702184383889 0.127 0.10063230242601535 0.252 0.4822465229287391 0.088 +2 0.23731750110449898 0.157 0.36283948286951195 0.127 0.11737528220270681 0.241 0.508006307979701 0.079 +3 0.23720772154428346 0.162 0.3413750625307264 0.13 0.11022341422239683 0.244 0.524770772536097 0.073 +4 0.23323617587127013 0.156 0.34983928159936833 0.127 0.07412956622825755 0.25 0.5189596580348228 0.072 +5 0.2361595377154521 0.161 0.3473391362060019 0.127 0.07544077838153962 0.248 0.5296109263845704 0.071 +6 0.23550548147984224 0.158 0.3298808913212924 0.129 0.0 0.0 0.524454031421209 0.064 diff --git a/papers/2011_emnlp_unsup_impact/figures/dv-wc-wordsi-pos-stkm.dat b/papers/2011_emnlp_unsup_impact/figures/dv-wc-wordsi-pos-stkm.dat new file mode 100644 index 00000000..c0703b5a --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/dv-wc-wordsi-pos-stkm.dat @@ -0,0 +1,1991 @@ +# term1 term2 pos simScore psdScore +elements musician NOUN 0.13576388685271545 0.524754 0.000663 +employment firm NOUN 0.17810232693909825 0.520116 0.000042 +elements link NOUN 0.11931139166911299 0.524248 0.000172 +evening oil NOUN 0.09690155091635708 0.539670 0.000169 +employees fans NOUN 0.20588850005209988 0.516869 0.000190 +entrance features NOUN 0.1687379944810093 0.537945 0.000589 +entertainment motion NOUN 0.07769865442051532 0.506912 0.000039 +error mechanism NOUN 0.1313312528185631 0.522871 0.000292 +equation patient NOUN 0.08626194443060291 0.502463 0.000045 +energy methods NOUN 0.16902676135062356 0.514523 0.000143 +elements factor NOUN 0.24383644689636727 0.520240 0.000235 +era founder NOUN 0.1684077377885326 0.502655 0.000051 +engineer judge NOUN 0.1659320764138995 0.505609 0.000169 +equipment method NOUN 0.29472839580948273 0.591100 0.001384 +element object NOUN 0.2262317827636071 0.510777 0.000049 +equipment input NOUN 0.1529916411597461 0.520072 0.000473 +entertainment food NOUN 0.15365928190642542 0.516723 0.000058 +entrance lines NOUN 0.18908814343982686 0.551243 0.000419 +engineer manufacturers NOUN 0.11811815491009549 0.531478 0.000173 +employment exchange NOUN 0.11508768358990398 0.502404 0.000126 +employment independence NOUN 0.09880197117453317 0.520521 0.000195 +element ice NOUN 0.11042339218749835 0.515522 0.000080 +episodes hit NOUN 0.12467062528300556 0.526195 0.000084 +environment extension NOUN 0.19959061239721837 0.511814 0.000050 +entrance facility NOUN 0.16805718065205508 0.515864 0.000237 +environment future NOUN 0.09477499287902177 0.522026 0.000418 +environment ideas NOUN 0.231890407591558 0.512320 0.000123 +election morning NOUN 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0.000482 +extension ocean NOUN 0.06832293462171374 0.513914 0.000177 +fan places NOUN 0.08436743329859062 0.536294 0.000826 +fashion objects NOUN 0.18428774671712192 0.532919 0.000478 +facilities manufacturers NOUN 0.24523364013658697 0.503954 0.000080 +files material NOUN 0.2658439429876566 0.517127 0.000560 +figures movement NOUN 0.20056908175677624 0.521238 0.000131 +festival performances NOUN 0.1430279429367249 0.534115 0.000206 +exposure fame NOUN 0.025431163559386034 0.515722 0.000065 +facility hotel NOUN 0.20233495084102443 0.512810 0.000131 +experiment functions NOUN 0.17123849162303073 0.523203 0.000149 +feature figures NOUN 0.27325924341722974 0.522941 0.000204 +facilities library NOUN 0.22155357467457143 0.513917 0.000494 +face parents NOUN 0.1480150618890098 0.577150 0.000205 +fight match NOUN 0.38060591111140135 0.506360 0.000059 +fight love NOUN 0.16574860298885014 0.547877 0.001213 +feature performance NOUN 0.15282701471410115 0.524582 0.000275 +experiment object NOUN 0.1918835409221528 0.515777 0.000251 +facilities passenger NOUN 0.17300786521941186 0.518567 0.000140 +features hunting NOUN 0.08365658736486044 0.550732 0.000340 +field hand NOUN 0.14793114701661841 0.588094 0.000813 +fire physics NOUN 0.10795062461091695 0.549725 0.000488 +fact kingdom NOUN 0.10021091142669558 0.537313 0.000092 +farm hospital NOUN 0.16637634902422496 0.525363 0.001095 +fleet involvement NOUN 0.20477291080202117 0.515464 0.000331 +father head NOUN 0.13055725583823147 0.584552 0.000333 +explanation picture NOUN 0.06389473117779852 0.533975 0.000292 +father marriage NOUN 0.1414443414340749 0.527544 0.000112 +firm offices NOUN 0.14505299050470744 0.509810 0.000133 +farmers immigrants NOUN 0.16707813840685737 0.512713 0.000102 +favor model NOUN 0.09786294659808309 0.543069 0.001666 +fleet interests NOUN 0.1701749908506135 0.531003 0.000185 +fields jobs NOUN 0.18942433986453736 0.501301 0.000287 +features industries NOUN 0.2723598444393853 0.522454 0.000154 +farmers leader NOUN 0.14627548194292497 0.530036 0.000455 +firm interests NOUN 0.13795672320751665 0.527597 0.000271 +factor function NOUN 0.18267618645394526 0.510775 0.000125 +exposure heat NOUN 0.21688395316607856 0.526679 0.000489 +explanation map NOUN 0.1494989607350913 0.520108 0.000095 +extension marriage NOUN 0.12974075976038352 0.579295 0.000450 +extent length NOUN 0.09834232853713067 0.569211 0.000274 +faith minority NOUN 0.12835339125808962 0.522950 0.000244 +exposure form NOUN 0.17403760542895552 0.525646 0.000432 +festival folk NOUN 0.5840282318736255 0.544508 0.000163 +fishing operations NOUN 0.09195478668564604 0.549895 0.000115 +farm league NOUN 0.07085203371131646 0.522566 0.000541 +favor king NOUN 0.12648698382495843 0.561692 0.000780 +father god NOUN 0.3182370907348626 0.548943 0.000058 +extension goals NOUN 0.09916090347928633 0.554610 0.000620 +farm mining NOUN 0.08945377514257914 0.520112 0.000134 +fame library NOUN 0.0338875177047951 0.525235 0.000283 +features makeup NOUN 0.0053941540695188 0.692655 0.032422 +fishing organizations NOUN 0.09426607695679504 0.529836 0.000108 diff --git a/papers/2011_emnlp_unsup_impact/figures/dv-wc-wordsi-scores-psd.dat b/papers/2011_emnlp_unsup_impact/figures/dv-wc-wordsi-scores-psd.dat new file mode 100644 index 00000000..9a446721 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/dv-wc-wordsi-scores-psd.dat @@ -0,0 +1,3 @@ +# segment k-means-f k-means-v spec-f spec-v cbc-f cbc-v online-f online-v +0 0.0 0.0 0.0 0.766361804509 0.161084197212 +1 0.0 0.0 0.0 0.0 diff --git a/papers/2011_emnlp_unsup_impact/figures/dv-wc-wordsi-scores-ukwac.dat b/papers/2011_emnlp_unsup_impact/figures/dv-wc-wordsi-scores-ukwac.dat new file mode 100644 index 00000000..876e7bdd --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/dv-wc-wordsi-scores-ukwac.dat @@ -0,0 +1,10 @@ +# segment k-means-f k-means-v spec-f spec-v cbc-f cbc-v online-f online-v +0 0.24099680857254557 0.149 0.33012197281452627 0.125 0.1015589587957502 0.25 0.4939821600371211 0.099 +1 0.23959296089909907 0.154 0.34445680832989356 0.129 0.10126513905564176 0.253 0.47707522888267706 0.09 +2 0.24244901184355377 0.153 0.3489722543052073 0.126 0.09589274447949968 0.251 0.47896955681883496 0.088 +3 0.23573781024436427 0.154 0.35943480375957837 0.13 0.10333837612458834 0.246 0.522902794019169 0.079 +4 0.23932881538452871 0.152 0.365501529317694 0.129 0.09941509102656786 0.25 0.5188049495822099 0.075 +5 0.23599724637731714 0.152 0.35406103129853334 0.125 0.09615895270783849 0.251 0.5199286803301583 0.068 +6 0.2812854101855288 0.148 0.33949693594075514 0.126 0.15019087031129197 0.241 0.5554235549597045 0.071 +7 0.27518015270941026 0.149 0.3565564260327844 0.124 0.15222994117691352 0.242 0.5716979123864533 0.069 +8 0.2757061335636379 0.149 0.36227704514967163 0.13 0.15224581283316097 0.242 0.5684436969163075 0.058 diff --git a/papers/2011_emnlp_unsup_impact/figures/dv-wc-wordsi-scores-wiki.dat b/papers/2011_emnlp_unsup_impact/figures/dv-wc-wordsi-scores-wiki.dat new file mode 100644 index 00000000..fc23a3c8 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/dv-wc-wordsi-scores-wiki.dat @@ -0,0 +1,8 @@ +# segment k-means-f k-means-v spec-f spec-v cbc-f cbc-v online-f online-v +0 0.2373555387627055 0.154 0.340509620167408 0.13 0.10351969075407183 0.251 0.0 0.0 +1 0.23645772392857003 0.152 0.3456903727119435 0.131 0.10127567655330828 0.254 0.47327079910143227 0.083 +2 0.24952328546651253 0.143 0.34515335586062884 0.126 0.11816759679697225 0.241 0.4748982298969292 0.09 +3 0.2395338380071576 0.159 0.3399282582981846 0.128 0.11127225075471205 0.243 0.5245567655954732 0.077 +4 0.23250032325993425 0.155 0.34909446183588916 0.125 0.10552098110090846 0.248 0.5188386058457585 0.075 +5 0.23295283393096874 0.156 0.35581519545080265 0.131 0.12642278745996777 0.239 0.5182819831155318 0.07 +6 0.23443258708238437 0.16 0.3337665092787791 0.123 0.0 0.0 0.5272215008591209 0.069 diff --git a/papers/2011_emnlp_unsup_impact/figures/dv-wc-wordsi-stkm.dat b/papers/2011_emnlp_unsup_impact/figures/dv-wc-wordsi-stkm.dat new file mode 100644 index 00000000..e9c9140f --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/dv-wc-wordsi-stkm.dat @@ -0,0 +1,2978 @@ +# term1 term2 pos simScore psdScore +electricity models NOUN 0.20810496784429675 0.950185 0.000528 +form manner NOUN 0.1851047479963407 0.797773 0.048396 +evening newspapers NOUN 0.0932991082629685 0.856471 0.028160 +format mind NOUN 0.11827106092170471 0.879720 0.021878 +format image NOUN 0.298306741145858 0.954632 0.000312 +event fashion NOUN 0.15086971906638086 0.793490 0.040315 +fight loss NOUN 0.19749178333359527 0.869430 0.033415 +enemies organizations NOUN 0.1913118212728722 0.860451 0.028377 +episodes feet NOUN 0.29271959716115575 0.868690 0.022242 +element genus NOUN 0.13837368161931166 0.887331 0.032717 +everything failure NOUN 0.10317752890638827 0.956030 0.000075 +feature phenomenon NOUN 0.20567263349439072 0.985273 0.000080 +feet minutes NOUN 0.4833099095809491 0.859588 0.016281 +engineer parish NOUN 0.34030584080049703 0.959367 0.000358 +features industries NOUN 0.2723598444393853 0.932438 0.002672 +fight periods NOUN 0.1325840720930856 0.970741 0.000084 +elections festival NOUN 0.2863457231874849 0.976272 0.000070 +emperor empire NOUN 0.7297363915877593 0.875852 0.034187 +energy oxygen NOUN 0.2502036525946724 0.954054 0.000044 +estate functions NOUN 0.1008433449814665 0.940764 0.001407 +enemies issues NOUN 0.27593956371134276 0.954391 0.000290 +features object NOUN 0.2402946905627049 0.937688 0.001224 +foot limits NOUN 0.18730665455901216 0.952734 0.000380 +engines items NOUN 0.12979364522487277 0.768969 0.032736 +food insurance NOUN 0.14410230829700582 0.943226 0.000169 +form lead NOUN 0.1126755250636777 0.886885 0.033248 +features page NOUN 0.11926190859477839 0.948245 0.000335 +forest park NOUN 0.4383656906778442 0.964357 0.000150 +form ones NOUN 0.29032298937850537 0.968935 0.000041 +environment estate NOUN 0.05488344920365715 0.875050 0.033024 +features move NOUN 0.19254428911690505 0.876943 0.019615 +fight peace NOUN 0.09694486927344653 0.976854 0.000118 +fiction museum NOUN 0.21201057739121487 0.982772 0.000053 +employees feet NOUN 0.20118377335649373 0.951642 0.000611 +elements input NOUN 0.13378624469424436 0.967248 0.000159 +everything one NOUN 0.330283768201478 0.966125 0.000130 +features nations NOUN 0.14885811927159798 0.947959 0.000221 +form jurisdiction NOUN 0.23311899162686897 0.968628 0.000094 +equation instance NOUN 0.1570095065320288 0.796663 0.053991 +element issues NOUN 0.20276796292134758 0.952901 0.000297 +feature issues NOUN 0.15323467845532548 0.886006 0.026060 +emperor person NOUN 0.10407060390213521 0.968321 0.000100 +evidence past NOUN 0.14616030704863983 0.807796 0.043886 +examples homes NOUN 0.14971825111059317 0.794088 0.039981 +employment marriage NOUN 0.1338986031092246 0.894473 0.022370 +episodes pages NOUN 0.22446969050712795 0.954218 0.000530 +evening news NOUN 0.17038893779087935 0.783884 0.034896 +estate pair NOUN 0.05188157610974246 0.971360 0.000198 +fear need NOUN 0.4520789524410063 0.785557 0.049135 +focus object NOUN 0.22721635430409207 0.957114 0.000434 +element influences NOUN 0.2093023616642291 0.959712 0.000267 +fear pain NOUN 0.1836584222268164 0.954723 0.000271 +election fall NOUN 0.2456795003871713 0.505511 0.000021 +election move NOUN 0.09900892568025475 0.971454 0.000331 +error maximum NOUN 0.1306215085705911 0.970246 0.000351 +environment partner NOUN 0.15699151650824206 0.953039 0.000632 +enemies gas NOUN 0.23814359514604203 0.862725 0.023946 +environment farmers NOUN 0.16026772921504367 0.959652 0.000141 +environment medium NOUN 0.16566649100090322 0.783075 0.051909 +end parts NOUN 0.22183831343372276 0.969758 0.000054 +fight friends NOUN 0.1575557855404758 0.965452 0.000157 +employees fire NOUN 0.1330597959702655 0.863850 0.022703 +food participants NOUN 0.16302314168549994 0.868225 0.029363 +end farm NOUN 0.21722183648097212 0.966183 0.000137 +evidence explanation NOUN 0.23130563739484392 0.891483 0.015910 +election governor NOUN 0.18433610749256396 0.787924 0.052173 +everything hand NOUN 0.10187440807765867 0.967619 0.000030 +favor movement NOUN 0.11676393927690075 0.887208 0.036988 +employees governments NOUN 0.19658652640711355 0.955912 0.000326 +elements logic NOUN 0.17372669718212744 0.949684 0.000155 +elements industries NOUN 0.3320161048736374 0.763345 0.033159 +engineer operations NOUN 0.20585062181996025 0.960152 0.000196 +feet meters NOUN 0.8429028412444961 0.875663 0.008229 +example living NOUN 0.028744216797220404 0.905477 0.008139 +example passage NOUN 0.23011245206397216 0.888822 0.033868 +everything none NOUN 0.04109325956809943 0.858516 0.036377 +engines facilities NOUN 0.16522975809381957 0.916433 0.002082 +example past NOUN 0.20982610252113712 0.789057 0.053463 +fight incident NOUN 0.3247469812904211 0.880609 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0.1837239077181109 0.654354 0.000460 +example murder NOUN 0.11387669157701831 0.749199 0.002254 +electricity images NOUN 0.17961518891192613 0.613744 0.000124 +episodes examples NOUN 0.2693858373975107 0.698236 0.000183 +entertainment insurance NOUN 0.16695519042067547 0.623553 0.000341 +enemies parents NOUN 0.17372166124474558 0.586573 0.002744 +energy function NOUN 0.16853342244598118 0.612409 0.000617 +engineer master NOUN 0.10503241588900421 0.563045 0.004097 +electricity equipment NOUN 0.18370524277440378 0.573582 0.000295 +evolution patterns NOUN 0.17577349412884108 0.622607 0.000244 +equipment gun NOUN 0.09904629482254712 0.651011 0.000276 +environment implementation NOUN 0.27410621528119894 0.630983 0.000392 +event instance NOUN 0.25152050106269597 0.584560 0.000022 +example friend NOUN 0.17637863410910581 0.749800 0.006150 +equipment maintenance NOUN 0.2559752168522365 0.583000 0.000376 +equipment infrastructure NOUN 0.2879405932903789 0.587505 0.000053 +example performance NOUN 0.23223946016248914 0.686324 0.001158 +employment license NOUN 0.09127247878758814 0.650546 0.000508 +equipment functions NOUN 0.2233508126561405 0.614297 0.000184 +equipment parent NOUN 0.08744400004141596 0.660561 0.000433 +elections event NOUN 0.3081396785774584 0.671506 0.000196 +example limits NOUN 0.14502820697452873 0.737907 0.001551 +enemies others NOUN 0.23784490811448256 0.617497 0.000142 +enemies features NOUN 0.2245277112075607 0.649639 0.000248 +example person NOUN 0.24198228934276805 0.706371 0.001152 diff --git a/papers/2011_emnlp_unsup_impact/figures/dv-wordsi-rel-scores-psd.dat b/papers/2011_emnlp_unsup_impact/figures/dv-wordsi-rel-scores-psd.dat new file mode 100644 index 00000000..62aca4bc --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/dv-wordsi-rel-scores-psd.dat @@ -0,0 +1,3 @@ +# segment k-means-f k-means-v spec-f spec-v cbc-f cbc-v online-f online-v +0 0.0 0.0 0.0 0.78574117865 0.146213151022 +1 0.0 0.0 0.0 0.0 diff --git a/papers/2011_emnlp_unsup_impact/figures/dv-wordsi-rel-scores-ukwac.dat b/papers/2011_emnlp_unsup_impact/figures/dv-wordsi-rel-scores-ukwac.dat new file mode 100644 index 00000000..1c99f624 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/dv-wordsi-rel-scores-ukwac.dat @@ -0,0 +1,10 @@ +# segment k-means-f k-means-v spec-f spec-v cbc-f cbc-v online-f online-v +0 0.6168499780410607 0.026 0.34996606612596187 0.099 0.5984541389113184 0.029 0.42070649483011785 0.114 +1 0.0 0.0 0.29446568434857573 0.105 0.5973192045364485 0.03 0.4263025118286027 0.111 +2 0.6182347644260046 0.025 0.3082838861560848 0.099 0.606680987526181 0.027 0.434622969048288 0.106 +3 0.6182347644260046 0.025 0.3209818083128649 0.102 0.6066643650021947 0.027 0.4396114017059777 0.102 +4 0.6182347644260046 0.025 0.30988367485974805 0.101 0.6064144576155893 0.027 0.4519521696665746 0.107 +5 0.6182347644260046 0.025 0.2879237096781659 0.112 0.6064327834936453 0.027 0.44665651473456414 0.102 +6 0.6182347644260046 0.025 0.3161541493892068 0.106 0.6066828466629944 0.027 0.4660530039787947 0.1 +7 0.6182347644260046 0.025 0.27736352962896393 0.111 0.6065503232083772 0.027 0.47925044999629635 0.103 +8 0.6182347644260046 0.025 0.30397945631565915 0.115 0.6065759122790711 0.027 0.47005051219811417 0.103 diff --git a/papers/2011_emnlp_unsup_impact/figures/dv-wordsi-rel-scores-wiki.dat b/papers/2011_emnlp_unsup_impact/figures/dv-wordsi-rel-scores-wiki.dat new file mode 100644 index 00000000..42c7dc06 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/dv-wordsi-rel-scores-wiki.dat @@ -0,0 +1,8 @@ +# segment k-means-f k-means-v spec-f spec-v cbc-f cbc-v online-f online-v +0 0.6169394515247332 0.026 0.30006338867666854 0.107 0.5983334034535096 0.029 0.3696820597461022 0.12 +1 0.20259039529214476 0.151 0.2753280705046053 0.108 0.6064228314061885 0.027 0.4308630813292238 0.109 +2 0.2041852438710118 0.149 0.2904887178693322 0.111 0.606538536740226 0.027 0.428446487711971 0.105 +3 0.2000931627629596 0.149 0.26301834098561244 0.115 0.6065344824541671 0.027 0.4396338345765405 0.106 +4 0.20499087613779554 0.15 0.2943617929001189 0.107 0.6065847624057844 0.027 0.0 0.0 +5 0.6182347644260046 0.025 0.2849325491137123 0.117 0.6065315246002058 0.027 0.4632301283274237 0.105 +6 0.6182347644260046 0.025 0.27408224438643425 0.113 0.6066635870633076 0.027 0.45631449535191093 0.101 diff --git a/papers/2011_emnlp_unsup_impact/figures/dv-wordsi-rel-stkm.dat b/papers/2011_emnlp_unsup_impact/figures/dv-wordsi-rel-stkm.dat new file mode 100644 index 00000000..cbb5c791 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/dv-wordsi-rel-stkm.dat @@ -0,0 +1,4571 @@ +# term1 term2 pos simScore psdScore +expansion move NOUN 0.17857811130419268 0.891326 0.036901 +elements maps NOUN 0.22438098708997709 0.981072 0.000070 +features nations NOUN 0.14885811927159798 0.976837 0.000012 +equation material NOUN 0.09161831370482924 0.798391 0.056198 +forest intelligence NOUN 0.1585170518151146 0.992484 0.000033 +experience plane NOUN 0.10176883802472894 0.795933 0.056613 +episodes match NOUN 0.1672617256053725 0.896224 0.034952 +fans lyrics NOUN 0.18722371001112323 0.989979 0.000054 +farmers leader NOUN 0.14627548194292497 0.896376 0.039366 +fight opening NOUN 0.17969048709846974 0.894895 0.038967 +episode games NOUN 0.18824317732119067 0.899349 0.034451 +feet half NOUN 0.10335647682343417 0.895164 0.039120 +examples performance NOUN 0.27488221812525854 0.985676 0.000048 +fame farm NOUN 0.07491010756645106 0.893572 0.038526 +facilities jobs NOUN 0.24385596947601962 0.889601 0.032744 +elements novel NOUN 0.1873588730499334 0.990983 0.000029 +extension negotiations NOUN 0.18308069113651596 0.893762 0.037871 +engineer musician NOUN 0.11957093310001987 0.889234 0.038187 +enemy fire NOUN 0.14661134452343969 0.894263 0.037136 +files manufacturers NOUN 0.2043513437779942 0.791713 0.053486 +experiment mission NOUN 0.21858041194105823 0.892192 0.037691 +episodes occasions NOUN 0.25224426553818935 0.971952 0.000120 +extension legislation NOUN 0.13407622671180802 0.990985 0.000014 +faith morning NOUN 0.12054137885232045 0.893355 0.038230 +engineer justice NOUN 0.2888750236735259 0.897315 0.034833 +followers god NOUN 0.208412215528656 0.694812 0.059104 +employees fans NOUN 0.20588850005209988 0.983482 0.000018 +examples metres NOUN 0.15433091050139008 0.796902 0.055849 +experiments mathematics NOUN 0.20460947552859604 0.885039 0.033941 +environment materials NOUN 0.1553146669254634 0.893709 0.034528 +fall places NOUN 0.10148239151773769 0.800040 0.052251 +fish involvement NOUN 0.1273586013948714 0.988991 0.000062 +forces mainland NOUN 0.05681039219868362 0.896576 0.037047 +farm model NOUN 0.1533349982190086 0.796196 0.054807 +features gas NOUN 0.1713823967074708 0.985763 0.000035 +followers founding NOUN 0.09980693268597098 0.797856 0.056180 +episodes houses NOUN 0.183223709044642 0.799058 0.054052 +facilities mass NOUN 0.21250564706463895 0.885085 0.038141 +emperor mother NOUN 0.15828568462503945 0.896593 0.038764 +fight peace NOUN 0.09694486927344653 0.799599 0.055454 +enemies forms NOUN 0.198401757328733 0.893545 0.037369 +food parent NOUN 0.08334303554451343 0.891413 0.039282 +employment justice NOUN 0.1008275922200821 0.990283 0.000041 +expansion passengers NOUN 0.1250374524424881 0.893093 0.038567 +fields industries NOUN 0.21105389406590142 0.989190 0.000032 +extension graduate NOUN 0.10769930933325272 0.992487 0.000014 +elements movement NOUN 0.19028159133368325 0.802004 0.054920 +experience journey NOUN 0.17320799552883745 0.789616 0.055168 +file method NOUN 0.1362802790506072 0.793007 0.057767 +experience manner NOUN 0.1367896258624173 0.995486 0.000018 +energy increase NOUN 0.1534252611376862 0.996494 0.000007 +form movie NOUN 0.15346824156813207 0.897133 0.037669 +files particles NOUN 0.10604277916212264 0.989283 0.000023 +employees forest NOUN 0.14784499123418543 0.890636 0.037174 +experience funds NOUN 0.13565602244500635 0.988776 0.000028 +expansion introduction NOUN 0.18529510129772941 0.895190 0.039158 +features genre NOUN 0.18078742403229356 0.990170 0.000073 +election jurisdiction NOUN 0.2215439356257436 0.892707 0.038882 +engines mixture NOUN 0.1593978939013936 0.994998 0.000005 +experience nickname NOUN 0.1553380569352458 0.899589 0.037875 +face fear NOUN 0.13396417676706082 0.794291 0.058437 +experience past NOUN 0.1800017547280759 0.800381 0.057480 +fish meat NOUN 0.2812704533305088 0.991283 0.000008 +end mouth NOUN 0.2823709850118857 0.894926 0.039069 +equipment noise NOUN 0.1633357573694244 0.990687 0.000065 +feet note NOUN 0.13727894481021405 0.986071 0.000046 +existence eye NOUN 0.15812745554245147 0.895322 0.039134 +environment growth NOUN 0.16677050924148576 0.701192 0.054120 +feet members NOUN 0.16288688770048984 0.896092 0.038359 +error mind NOUN 0.14090967991237002 0.702535 0.056835 +exposure networks NOUN 0.17959971533255117 0.890079 0.031907 +facility merchant NOUN 0.0747502261134573 0.888549 0.081043 +father job NOUN 0.20214111377408664 0.896034 0.039577 +employees ministers NOUN 0.14708020821340498 0.991755 0.000038 +explanation limits NOUN 0.15951081240091755 0.799880 0.056392 +era movements NOUN 0.1415538485029715 0.796975 0.056954 +facility farm NOUN 0.19739997456915814 0.892314 0.037351 +features needs NOUN 0.24354254157137598 0.895639 0.030422 +focus influence NOUN 0.26142498314732593 0.892664 0.036041 +followers organizations NOUN 0.19118573928193205 0.898948 0.031443 +floor meters NOUN 0.1979763230990213 0.795816 0.055370 +favor majority NOUN 0.08717550490203634 0.699820 0.059807 +extension map NOUN 0.18336988220624992 0.989880 0.000032 +equipment lack NOUN 0.17019541405990446 0.899680 0.037316 +fire mission NOUN 0.15271684375503117 0.794674 0.059163 +enemy guard NOUN 0.10668231397484972 0.995111 0.000016 +focus ideas NOUN 0.23989931761251818 0.895643 0.034959 +format method NOUN 0.2508530511809197 0.881062 0.034550 +environment phase NOUN 0.17137478625422564 0.982781 0.000019 +episode half NOUN 0.10446821036960666 0.989482 0.000053 +error information NOUN 0.1413008904417772 0.897246 0.033139 +focus motor NOUN 0.10782139032792436 0.897577 0.037896 +fishing forest NOUN 0.109944967004032 0.886175 0.037394 +eye operators NOUN 0.14074002717393624 0.991411 0.000010 +experience models NOUN 0.25964816435365523 0.981374 0.000198 +features pair NOUN 0.17856922470433415 0.989166 0.000109 +fact failure NOUN 0.10926365666287276 0.916667 0.000070 +fire forest NOUN 0.12525940737979385 0.992590 0.000016 +examples month NOUN 0.16377024240601132 0.789758 0.053338 +food manufacturers NOUN 0.1921809823584802 0.789247 0.051590 +evening logo NOUN 0.09135718788961023 0.791592 0.056345 +file material NOUN 0.15762617231880133 0.798798 0.054722 +empire involvement NOUN 0.09749476986717312 0.993693 0.000013 +experience experiments NOUN 0.19203624798072516 0.889178 0.035678 +farmers followers NOUN 0.21017204056551886 0.790011 0.056246 +force ground NOUN 0.1137682527573098 0.894135 0.038878 +exposure limits NOUN 0.15341390978863817 0.989386 0.000050 +facilities missions NOUN 0.17135633173406317 0.893873 0.037194 +forest north NOUN 0.22677096521556564 0.806087 0.056246 +flag origin NOUN 0.18428154964911247 0.984852 0.000187 +emphasis needs NOUN 0.1683590765618307 0.893930 0.038757 +feature issue NOUN 0.16393117538895213 0.992485 0.000028 +festival journalist NOUN 0.16485874235799253 0.994089 0.000006 +features jobs NOUN 0.19582455714902972 0.974942 0.000144 +episode fight NOUN 0.19146739930467768 0.795332 0.056995 +form opinion NOUN 0.11475005215688365 0.989968 0.000028 +employment official NOUN 0.15882384482146047 0.893040 0.038599 +elements means NOUN 0.2737910589422615 0.799399 0.055895 +folk lead NOUN 0.09231137758138915 0.890858 0.037712 +elements influences NOUN 0.39877589324618257 0.892600 0.035779 +features interest NOUN 0.19697792861913715 0.904652 0.029707 +fame honor NOUN 0.057471132846389196 0.792610 0.054752 +expansion investment NOUN 0.14205560901664896 0.889713 0.039275 +error mode NOUN 0.14667730934628764 0.887064 0.036081 +episodes model NOUN 0.19538702693266868 0.896324 0.035942 +followers groups NOUN 0.22036153512442658 0.982581 0.000071 +elements phrase NOUN 0.19906730440574677 0.897053 0.036464 +entertainment motor NOUN 0.15354099525274453 0.982981 0.000064 +exile gold NOUN 0.06506558109122632 0.701663 0.055559 +feet municipalities NOUN 0.16758101347870005 0.708421 0.055517 +followers months NOUN 0.16131584160521345 0.891259 0.032781 +figures mythology NOUN 0.05811250008512508 0.961450 0.000268 +exposure levels NOUN 0.27851720726232665 0.982086 0.000118 +episodes movie NOUN 0.2510517804011711 0.896963 0.037499 +experiment information NOUN 0.17947560940575155 0.972973 0.000203 +explanation incident NOUN 0.226667762142719 0.984167 0.000013 +era historian NOUN 0.18911417938313793 0.703960 0.056105 +error frequency NOUN 0.13421358239968392 0.885128 0.037144 +face legs NOUN 0.16625450605015415 0.993791 0.000008 +elections jobs NOUN 0.14109289758237556 0.992494 0.000035 +face love NOUN 0.15268660662030872 0.792668 0.058107 +feature form NOUN 0.23561526804922275 0.898587 0.038217 +explanation names NOUN 0.28348716987061107 0.896669 0.032068 +focus function NOUN 0.22553571334897138 0.894768 0.034064 +exchange infrastructure NOUN 0.08103762616420229 0.988781 0.000029 +form measure NOUN 0.2099122065310822 0.994478 0.000033 +farm hunting NOUN 0.09857048659996577 0.987190 0.000038 +fight move NOUN 0.25687298619782073 0.890825 0.036954 +fight instance NOUN 0.176598481835126 0.848373 0.004926 +form historian NOUN 0.22293515613881545 0.699498 0.056348 +forces personnel NOUN 0.36059024426088726 0.893440 0.034363 +employment partner NOUN 0.14354134360854445 0.895206 0.036104 +existence kingdom NOUN 0.3623841085171996 0.600781 0.038801 +field models NOUN 0.13089000145812513 0.990592 0.000129 +exile month NOUN 0.13552285814490303 0.975446 0.000282 +format location NOUN 0.17333461337114045 0.799760 0.054249 +enemies involvement NOUN 0.25881246410818776 0.794790 0.057996 +followers hands NOUN 0.13442281047716853 0.701322 0.057906 +elements experiments NOUN 0.24182865555999172 0.886172 0.035301 +forest heritage NOUN 0.09279651441899506 0.895053 0.038941 +entrance hospital NOUN 0.1505843348760211 0.795377 0.056394 +files material NOUN 0.2658439429876566 0.987380 0.000019 +favor mark NOUN 0.10214214138739784 0.898258 0.037161 +features form NOUN 0.35258488187150394 0.894541 0.036714 +experience individual NOUN 0.2312505640399351 0.891372 0.037390 +farm land NOUN 0.06050835334604165 0.896635 0.037402 +fans hall NOUN 0.08214592098818958 0.700180 0.058680 +entrance half NOUN 0.10988076168496483 0.698468 0.058930 +element functions NOUN 0.20389371637649237 0.898385 0.034627 +fashion host NOUN 0.14124397038270528 0.898247 0.039155 +experience person NOUN 0.2231589511686679 0.799639 0.058123 +extension lines NOUN 0.21286072891392727 0.891797 0.040838 +fleet islands NOUN 0.3428472192044406 0.699990 0.057020 +fact kind NOUN 0.09447165445319476 0.916775 0.000073 +era facilities NOUN 0.14010445135656224 0.886329 0.035813 +element night NOUN 0.14269585319710718 0.801362 0.053951 +episodes images NOUN 0.24005889190230562 0.800441 0.052081 +employees employment NOUN 0.24108419887019328 0.993293 0.000008 +experiments fiction NOUN 0.17502570981221763 0.885995 0.034124 +flag hero NOUN 0.44293700881869646 0.897015 0.039278 +estate houses NOUN 0.06003431829166051 0.799379 0.056656 +electricity funding NOUN 0.15818340372804948 0.793439 0.055747 +favor love NOUN 0.11234257332390672 0.703095 0.057530 +entrance feature NOUN 0.15892364772635068 0.994594 0.000015 +facilities key NOUN 0.1351875807274992 0.984571 0.000090 +feet frequency NOUN 0.12933687613531766 0.798258 0.057194 +facilities motor NOUN 0.0917229948428226 0.991189 0.000019 +files frame NOUN 0.11667631837843792 0.900441 0.034084 +environment planet NOUN 0.13837581871760457 0.798077 0.057841 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ifelse } + {dup dup 0 get findfont exch 1 get scalefont setfont + [ currentpoint ] exch dup 2 get 0 exch R dup 5 get 2 ne {dup dup 6 + get exch 4 get {Gshow} {stringwidth pop 0 R} ifelse }if dup 5 get 0 eq + {dup 3 get {2 get neg 0 exch R pop} {pop aload pop M} ifelse} {dup 5 + get 1 eq {dup 2 get exch dup 3 get exch 6 get stringwidth pop -2 div + dup 0 R} {dup 6 get stringwidth pop -2 div 0 R 6 get + show 2 index {aload pop M neg 3 -1 roll neg R pop pop} {pop pop pop + pop aload pop M} ifelse }ifelse }ifelse } + ifelse } + forall} def +/Gswidth {dup type /stringtype eq {stringwidth} {pop (n) stringwidth} ifelse} def +/MFwidth {0 exch { dup 5 get 3 ge { 5 get 3 eq { 0 } { pop } ifelse } + {dup 3 get{dup dup 0 get findfont exch 1 get scalefont setfont + 6 get Gswidth pop add} {pop} ifelse} ifelse} forall} def +/MLshow { currentpoint stroke M + 0 exch R + Blacktext {gsave 0 setgray MFshow grestore} {MFshow} ifelse } bind def +/MRshow { currentpoint stroke M + exch dup MFwidth neg 3 -1 roll R + Blacktext {gsave 0 setgray MFshow grestore} {MFshow} ifelse } bind def +/MCshow { currentpoint stroke M + exch dup MFwidth -2 div 3 -1 roll R + Blacktext {gsave 0 setgray MFshow grestore} {MFshow} ifelse } bind def +/XYsave { [( ) 1 2 true false 3 ()] } bind def +/XYrestore { [( ) 1 2 true false 4 ()] } bind def +end +%%EndProlog +gnudict begin +gsave +doclip +50 50 translate +0.050 0.050 scale +0 setgray +newpath +(Helvetica) findfont 240 scalefont setfont +1.000 UL +LTb +935 2772 M +63 0 V +2457 0 R +-63 0 V +stroke +791 2772 M +[ [(Helvetica) 240.0 0.0 true true 0 (0.00)] +] -80.0 MRshow +1.000 UL +LTb +935 3066 M +63 0 V +2457 0 R +-63 0 V +stroke +791 3066 M +[ [(Helvetica) 240.0 0.0 true true 0 (0.05)] +] -80.0 MRshow +1.000 UL +LTb +935 3360 M +63 0 V +2457 0 R +-63 0 V +stroke +791 3360 M +[ [(Helvetica) 240.0 0.0 true true 0 (0.10)] +] -80.0 MRshow +1.000 UL +LTb +935 3654 M +63 0 V +2457 0 R +-63 0 V +stroke +791 3654 M +[ [(Helvetica) 240.0 0.0 true true 0 (0.15)] 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[(Helvetica) 240.0 0.0 true true 0 ( 0)] +] -80.0 MCshow +1.000 UL +LTb +4380 655 M +0 63 V +0 1701 R +0 -63 V +stroke +4380 415 M +[ [(Helvetica) 240.0 0.0 true true 0 ( 1)] +] -80.0 MCshow +1.000 UL +LTb +4800 655 M +0 63 V +0 1701 R +0 -63 V +stroke +4800 415 M +[ [(Helvetica) 240.0 0.0 true true 0 ( 2)] +] -80.0 MCshow +1.000 UL +LTb +5220 655 M +0 63 V +0 1701 R +0 -63 V +stroke +5220 415 M +[ [(Helvetica) 240.0 0.0 true true 0 ( 3)] +] -80.0 MCshow +1.000 UL +LTb +5639 655 M +0 63 V +0 1701 R +0 -63 V +stroke +5639 415 M +[ [(Helvetica) 240.0 0.0 true true 0 ( 4)] +] -80.0 MCshow +1.000 UL +LTb +6059 655 M +0 63 V +0 1701 R +0 -63 V +stroke +6059 415 M +[ [(Helvetica) 240.0 0.0 true true 0 ( 5)] +] -80.0 MCshow +1.000 UL +LTb +6479 655 M +0 63 V +0 1701 R +0 -63 V +stroke +6479 415 M +[ [(Helvetica) 240.0 0.0 true true 0 ( 6)] +] -80.0 MCshow +1.000 UL +LTb +1.000 UL +LTb +3960 2419 N +0 -1764 V +2519 0 V +0 1764 V +-2519 0 V +Z stroke +LCb setrgbcolor +5219 55 M +[ [(Helvetica) 240.0 0.0 true true 0 (Segment Number)] +] -80.0 MCshow +LTb +2.000 UP +1.000 UL +LTb +% Begin plot #1 +2.000 UP +1.000 UL +LT0 +1.00 0.00 0.00 C 3960 1186 M +420 -11 V +420 3 V +420 0 V +419 -9 V +420 7 V +420 -2 V +3960 1186 Star +4380 1175 Star +4800 1178 Star +5220 1178 Star +5639 1169 Star +6059 1176 Star +6479 1174 Star +% End plot #1 +% Begin plot #2 +2.000 UP +1.000 UL +LT1 +0.00 1.00 0.00 C 3960 1396 M +420 43 V +420 16 V +420 -47 V +419 18 V +420 -5 V +420 -39 V +3960 1396 TriDF +4380 1439 TriDF +4800 1455 TriDF +5220 1408 TriDF +5639 1426 TriDF +6059 1421 TriDF +6479 1382 TriDF +% End plot #2 +% Begin plot #3 +2.000 UP +1.000 UL +LT2 +1.00 0.65 0.00 C 3960 881 M +420 -4 V +420 37 V +420 -16 V +419 -80 V +420 3 V +6479 655 L +3960 881 Dia +4380 877 Dia +4800 914 Dia +5220 898 Dia +5639 818 Dia +6059 821 Dia +6479 655 Dia +% End plot #3 +% Begin plot #4 +2.000 UP +1.000 UL +LT3 +0.75 0.50 1.00 C 3960 655 M +420 1063 V +420 57 V +420 37 V +419 -13 V +420 24 V +420 -12 V +3960 655 DiaF +4380 1718 DiaF +4800 1775 DiaF +5220 1812 DiaF +5639 1799 DiaF +6059 1823 DiaF +6479 1811 DiaF +% End plot #4 +1.000 UL +LTb +3960 2419 N +0 -1764 V +2519 0 V +0 1764 V +-2519 0 V +Z stroke +2.000 UP +1.000 UL +LTb +stroke +grestore +end +showpage +%%Trailer +%%DocumentFonts: Helvetica diff --git a/papers/2011_emnlp_unsup_impact/figures/pos-results.p b/papers/2011_emnlp_unsup_impact/figures/pos-results.p new file mode 100644 index 00000000..6f8f4f41 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/pos-results.p @@ -0,0 +1,85 @@ +set term postscript eps enhanced color lw 3 "Helvetica" 24 +set output 'pos-results.eps' +#set terminal png transparent nocrop enhanced font arial 8 size 500,350 +#set output 'pos-results.png' + +set pointsize 2 +set multiplot +set size 0.35,0.35 + +# FIXME: the key needs to go at the bottom of all the plots +unset key +#set key outside bottom center vertical noreverse enhanced autotitles nobox + +set xtics mirror +set format x "%2.0f" +set format y "%.2f" + +set yrange [ 0.0 : 0.30 ] noreverse nowriteback +set ylabel "V-Measure" +set format x '' +set title "ukWaC" + +set lmargin 0 +set rmargin 0 +set bmargin 0 +set tmargin 0 +set origin 0.13, 0.55 + +# UKWAC data +plot 'dv-wc-wordsi-pos-scores-ukwac.dat' using 1:3 title "K-Means V-Measure" ls 2 pt 3 lw 1 lc rgb "red" lt 1 axis x1y1 with linespoints, \ + 'dv-wc-wordsi-pos-scores-ukwac.dat' using 1:5 title "Spectra V-Measure" ls 2 pt 11 lw 1 lc rgb "green" lt 2 axis x1y1 with linespoints, \ + 'dv-wc-wordsi-pos-scores-ukwac.dat' using 1:7 title "CBC V-Measure" ls 2 pt 12 lw 1 lc rgb "orange" lt 3 axis x1y1 with linespoints, \ + 'dv-wc-wordsi-pos-scores-ukwac.dat' using 1:9 title "On-line K-Means V-Measure" ls 2 pt 13 lw 1 lc rgb "purple" lt 4 axis x1y1 with linespoints + +unset ylabel +set format y '' +set title "Wikipedia" +set origin 0.55, 0.55 + +# WIKIPEDIA +plot 'dv-wc-wordsi-pos-scores-wiki.dat' using 1:3 title "K-Means V-Measure" ls 2 pt 3 lw 1 lc rgb "red" lt 1 axis x1y1 with linespoints, \ + 'dv-wc-wordsi-pos-scores-wiki.dat' using 1:5 title "Spectra V-Measure" ls 2 pt 11 lw 1 lc rgb "green" lt 2 axis x1y1 with linespoints, \ + 'dv-wc-wordsi-pos-scores-wiki.dat' using 1:7 title "CBC V-Measure" ls 2 pt 12 lw 1 lc rgb "orange" lt 3 axis x1y1 with linespoints, \ + 'dv-wc-wordsi-pos-scores-wiki.dat' using 1:9 title "On-line K-Means V-Measure" ls 2 pt 13 lw 1 lc rgb "purple" lt 4 axis x1y1 with linespoints + +# remove the ukWaC and Wikipedia titles for the lower graphs +unset title +# add the xtic labeling back +set format x ' %g' +set format y ' %.2f' + +set xtics auto +set ylabel "Paired FScore" +set xlabel 'Segment Number' +# NOTE: this range should stay fixed across all result plots +# to ensure horizontal readability +set yrange [ 0.0 : 0.80 ] noreverse nowriteback + + +#set xrange [ 1 : 8 ] noreverse nowriteback +set ytics auto + +set origin 0.13, 0.13 + +# UKWAC +plot 'dv-wc-wordsi-pos-scores-ukwac.dat' using 1:2 title "K-Means F-Score" ls 1 pt 3 lw 1 lc rgb "red" lt 1 axis x1y1 with linespoints, \ + 'dv-wc-wordsi-pos-scores-ukwac.dat' using 1:4 title "Spectral F-Score" ls 1 pt 11 lw 1 lc rgb "green" lt 2 axis x1y1 with linespoints, \ + 'dv-wc-wordsi-pos-scores-ukwac.dat' using 1:6 title "CBC F-Score" ls 1 pt 12 lw 1 lc rgb "orange" lt 3 axis x1y1 with linespoints, \ + 'dv-wc-wordsi-pos-scores-ukwac.dat' using 1:8 title "On-line K-Means F-Score" ls 1 pt 13 lw 1 lc rgb "purple" lt 4 axis x1y1 with linespoints + +unset ylabel +set format y '' +set origin 0.55, 0.13 + +# WIKIPEDIA +plot 'dv-wc-wordsi-pos-scores-wiki.dat' using 1:2 title "K-Means F-Score" ls 1 pt 3 lw 1 lc rgb "red" lt 1 axis x1y1 with linespoints, \ + 'dv-wc-wordsi-pos-scores-wiki.dat' using 1:4 title "Spectral F-Score" ls 1 pt 11 lw 1 lc rgb "green" lt 2 axis x1y1 with linespoints, \ + 'dv-wc-wordsi-pos-scores-wiki.dat' using 1:6 title "CBC F-Score" ls 1 pt 12 lw 1 lc rgb "orange" lt 3 axis x1y1 with linespoints, \ + 'dv-wc-wordsi-pos-scores-wiki.dat' using 1:8 title "On-line K-Means F-Score" ls 1 pt 13 lw 1 lc rgb "purple" lt 4 axis x1y1 with linespoints + + + + + + diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/all-wcprops b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/all-wcprops new file mode 100644 index 00000000..08ad194d --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/all-wcprops @@ -0,0 +1,221 @@ +K 25 +svn:wc:ra_dav:version-url +V 53 +/depot/!svn/ver/801/papers/unsup_2011/figures/psd_dat +END +ResultsBinner.java +K 25 +svn:wc:ra_dav:version-url +V 72 +/depot/!svn/ver/801/papers/unsup_2011/figures/psd_dat/ResultsBinner.java +END +dv-wc-wordsi-order-stkm.dat +K 25 +svn:wc:ra_dav:version-url +V 81 +/depot/!svn/ver/797/papers/unsup_2011/figures/psd_dat/dv-wc-wordsi-order-stkm.dat +END +dv-wordsi-rel-scores-psd.dat +K 25 +svn:wc:ra_dav:version-url +V 82 +/depot/!svn/ver/797/papers/unsup_2011/figures/psd_dat/dv-wordsi-rel-scores-psd.dat +END +dv-wordsi-rel-gs-kmeans.dat +K 25 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+2011-05-19T19:19:27.027327Z +ecb60ff4859ec511ebb1d8be3e24367c +2011-05-19T19:10:31.614516Z +797 +jurgens + + + + + + + + + + + + + + + + + + + + + +72451 + diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/prop-base/ResultsBinner.class.svn-base b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/prop-base/ResultsBinner.class.svn-base new file mode 100644 index 00000000..5e9587e6 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/prop-base/ResultsBinner.class.svn-base @@ -0,0 +1,5 @@ +K 13 +svn:mime-type +V 24 +application/octet-stream +END diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/prop-base/ResultsBinner.java.svn-base b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/prop-base/ResultsBinner.java.svn-base new file mode 100644 index 00000000..138f9833 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/prop-base/ResultsBinner.java.svn-base @@ -0,0 +1,5 @@ +K 13 +svn:mime-type +V 10 +text/plain +END diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/prop-base/Stats.class.svn-base b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/prop-base/Stats.class.svn-base new file mode 100644 index 00000000..5e9587e6 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/prop-base/Stats.class.svn-base @@ -0,0 +1,5 @@ +K 13 +svn:mime-type +V 24 +application/octet-stream +END diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/prop-base/Stats.java.svn-base b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/prop-base/Stats.java.svn-base new file mode 100644 index 00000000..138f9833 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/prop-base/Stats.java.svn-base @@ -0,0 +1,5 @@ +K 13 +svn:mime-type +V 10 +text/plain +END diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/ResultsBinner.class.svn-base b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/ResultsBinner.class.svn-base new file mode 100644 index 00000000..ce3a8eed Binary files /dev/null and b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/ResultsBinner.class.svn-base differ diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/ResultsBinner.java.svn-base b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/ResultsBinner.java.svn-base new file mode 100644 index 00000000..9ac9002d --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/ResultsBinner.java.svn-base @@ -0,0 +1,41 @@ +import java.io.*; +import java.util.*; + +import edu.ucla.sspace.common.Statistics; + +public class ResultsBinner { + + public static void main(String[] args) throws Exception { + if (args.length < 1) { + System.out.println("usage: RB input.dat output.dat"); + return; + } + + List[] scores = new List[100]; + for (int i = 0; i < scores.length; ++i) + scores[i] = new ArrayList(); + + BufferedReader br = new BufferedReader(new FileReader(args[0])); + br.readLine(); + for (String line = null; (line = br.readLine()) != null; ) { + String[] arr = line.split("\\s+"); + if (arr.length != 6 || line.startsWith("#")) + continue; + double similarity = Double.parseDouble(arr[3]); + double psdAcc = Double.parseDouble(arr[4]); + int bucket = (int)(similarity * 100); + scores[bucket].add(psdAcc); + } + br.close(); + + for (int i = 0; i < scores.length; ++i) { + List s = (List)(scores[i]); + if (s.size() > 0) { + double stderr = (s.size() > 1 ? Statistics.stderr(s) : 0); + System.out.println(i + " " + Statistics.mean(s) + " " + + stderr + " " + s.size()); + } + } + } + +} \ No newline at end of file diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/Stats.class.svn-base b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/Stats.class.svn-base new file mode 100644 index 00000000..31a63dbe Binary files /dev/null and b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/Stats.class.svn-base differ diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/Stats.java.svn-base b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/Stats.java.svn-base new file mode 100644 index 00000000..91c98f15 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/Stats.java.svn-base @@ -0,0 +1,29 @@ +import java.io.*; +import java.util.*; + +import edu.ucla.sspace.common.Statistics; +import edu.ucla.sspace.util.LineReader; + +public class Stats { + + public static void main(String[] args) { +// List[] points = new List[60]; +// for (int i = 0; i < points.length; ++i) +// points[i] = new ArrayList(); + List numPoints = new ArrayList(); + for (String file : args) { + for (String line : new LineReader(new File(file))) { + String[] arr = line.split("\\s+"); + int i = Integer.parseInt(arr[0]); + if (i <= 60) + numPoints.add(Integer.parseInt(arr[3])); + } + } + + System.out.printf("Mean number of points %f, median %d (stddev %f)%n", + Statistics.mean(numPoints), + Statistics.median(numPoints), + Statistics.stddev(numPoints)); + } + +} \ No newline at end of file diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wc-wordsi-25-cbc.dat.svn-base b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wc-wordsi-25-cbc.dat.svn-base new file mode 100644 index 00000000..533fa2a2 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wc-wordsi-25-cbc.dat.svn-base @@ -0,0 +1,2610 @@ +# term1 term2 pos simScore psdScore +file layer NOUN 0.09665135369020475 0.886154 0.001311 +facilities grades NOUN 0.1050413854029532 0.892330 0.002454 +fleet house NOUN 0.09327143017196153 0.872847 0.000553 +facility homes NOUN 0.23300229084117977 0.861320 0.005933 +electricity manufacturers NOUN 0.14954562094522098 0.862826 0.003217 +election lack NOUN 0.12408058803891991 0.835286 0.001208 +files particles NOUN 0.10604277916212264 0.909155 0.002411 +explanation permission NOUN 0.3438017337599127 0.901921 0.002522 +engineer manufacturers NOUN 0.11811815491009549 0.886398 0.001666 +features others NOUN 0.13649688302201224 0.919382 0.001168 +file input NOUN 0.14431291368394544 0.909127 0.003867 +element layer NOUN 0.10740852239163833 0.898779 0.001275 +focus inspiration NOUN 0.1584991959210019 0.794348 0.007326 +festival meetings NOUN 0.40955785071176026 0.865138 0.001675 +firm offices NOUN 0.14505299050470744 0.915115 0.002567 +enemies experience NOUN 0.2518864764918647 0.882282 0.004094 +employment information NOUN 0.27804458785948566 0.921722 0.000488 +energy memory NOUN 0.1713719230516431 0.827141 0.008289 +eye infrastructure NOUN 0.16822953108338223 0.879067 0.000939 +extension format NOUN 0.24131374338950523 0.857071 0.001299 +focus location NOUN 0.2350800006639828 0.757260 0.004821 +explanation origin NOUN 0.19042621306180516 0.791010 0.001137 +forces guest NOUN 0.08624223989529328 0.781676 0.022131 +end limit NOUN 0.10958427885659856 0.756984 0.000171 +extent numbers NOUN 0.0879468139220409 0.819786 0.001413 +food items NOUN 0.19981483900862682 0.661625 0.039598 +flag forces NOUN 0.15886938864515052 0.762372 0.018190 +fire parks NOUN 0.16000706293920924 0.879592 0.001781 +films list NOUN 0.15963729577063368 0.901565 0.001805 +elements others NOUN 0.1396436613111732 0.858646 0.001036 +figures musicians NOUN 0.19831541999263955 0.806497 0.025371 +element features NOUN 0.27558060994891687 0.856326 0.005559 +employment honors NOUN 0.12570141167660825 0.914807 0.001019 +facilities homes NOUN 0.23061908204734222 0.899149 0.001208 +electricity model NOUN 0.1805896253512857 0.887601 0.000209 +facility farm NOUN 0.19739997456915814 0.757206 0.017171 +end farm NOUN 0.21722183648097212 0.894547 0.002823 +face foot NOUN 0.12221464224310036 0.864711 0.001195 +employees office NOUN 0.09453872557842892 0.878342 0.000427 +enemy model NOUN 0.1448329774580015 0.828343 0.001301 +films months NOUN 0.14980710298129493 0.837962 0.001806 +energy inspiration NOUN 0.18409675716398963 0.737296 0.010059 +enemies goals NOUN 0.09497066952742994 0.882542 0.004615 +electricity means NOUN 0.23498756171667612 0.908103 0.000142 +employees hospital NOUN 0.1585565129840222 0.892314 0.002007 +favor officials NOUN 0.09754003369552357 0.913078 0.000900 +features lyrics NOUN 0.1740506028342073 0.849343 0.000491 +employees member NOUN 0.19234834648373134 0.914480 0.001411 +emperor model NOUN 0.08322670532630436 0.862511 0.000361 +employees fire NOUN 0.1330597959702655 0.877365 0.000908 +flow frame NOUN 0.10864694326000965 0.752104 0.016035 +fear god NOUN 0.18206812287947238 0.884091 0.005356 +followers orders NOUN 0.17235052434335815 0.646228 0.031811 +focus ideas NOUN 0.23989931761251818 0.756935 0.017941 +facility hospital NOUN 0.23957933051848465 0.866406 0.004893 +feature motion NOUN 0.046973492710426154 0.817335 0.001550 +electricity information NOUN 0.1795555588889373 0.850390 0.001759 +face person NOUN 0.17473395393985852 0.873660 0.003206 +fish participants NOUN 0.18960041145016146 0.827117 0.000524 +explanation orders NOUN 0.1665313778517571 0.895618 0.002164 +elements images NOUN 0.3243490527199895 0.889579 0.001199 +fleet planet NOUN 0.1642683544885559 0.868142 0.002213 +field operations NOUN 0.12575762057727077 0.826457 0.001949 +followers inhabitants NOUN 0.2832994499861355 0.701602 0.028791 +features mechanism NOUN 0.2209149928368876 0.934863 0.000945 +films ones NOUN 0.20284202189156053 0.757345 0.006912 +face instance NOUN 0.14804987292918373 0.805208 0.024016 +extension guns NOUN 0.06654941442180015 0.892682 0.002881 +fight movement NOUN 0.20085830802519788 0.838542 0.003571 +firm officials NOUN 0.1791259584529727 0.934041 0.003170 +facilities faculty NOUN 0.12794634268228894 0.928993 0.000960 +elements limits NOUN 0.17295777861061143 0.837575 0.000891 +festival music NOUN 0.2399925599836181 0.823064 0.005908 +fishing operations NOUN 0.09195478668564604 0.784406 0.021414 +enemies future NOUN 0.11815163449515191 0.902515 0.005966 +films performance NOUN 0.20983529718262198 0.786387 0.000764 +films friends NOUN 0.13615093064411954 0.778346 0.007352 +employees official NOUN 0.2166571870956801 0.878093 0.001920 +emphasis losses NOUN 0.18793640323731045 0.972464 0.000039 +elements instrument NOUN 0.22122668914618313 0.831714 0.004060 +explanation opportunity NOUN 0.243424096285671 0.806293 0.029094 +employees maintenance NOUN 0.16703899606711878 0.877065 0.002544 +features memory NOUN 0.20839279123255047 0.879663 0.001006 +figures forms NOUN 0.2109599949725277 0.868650 0.005262 +elements paintings NOUN 0.1879301287675249 0.882801 0.001494 +facilities mass NOUN 0.21250564706463895 0.914314 0.000209 +exposure medium NOUN 0.17475216574443436 0.794353 0.023672 +features methods NOUN 0.3254169845248618 0.927289 0.000481 +elements mainstream NOUN 0.15306037473680034 0.890960 0.001652 +fear fight NOUN 0.2604565010311166 0.882824 0.004145 +end independence NOUN 0.1096690347212033 0.862490 0.000202 +fiction movie NOUN 0.06507613270167863 0.809261 0.025933 +exposure level NOUN 0.15664001556625973 0.919799 0.002807 +feet participants NOUN 0.13690386134534066 0.919610 0.002592 +elements musician NOUN 0.13576388685271545 0.869613 0.005073 +films picture NOUN 0.11702415666061365 0.835038 0.002133 +engines motor NOUN 0.10897162760711274 0.809085 0.000475 +figures officials NOUN 0.21800486019584134 0.785478 0.023433 +features form NOUN 0.35258488187150394 0.919426 0.001023 +empire faith NOUN 0.09449427470045013 0.867696 0.001294 +fight form NOUN 0.19030513465085203 0.807396 0.009230 +fight pair NOUN 0.18550128424453102 0.875376 0.003139 +enemy opponent NOUN 0.22662733773100432 0.890124 0.002980 +elections newspapers NOUN 0.1917517594578362 0.865138 0.004131 +enemies influence NOUN 0.27406666286609044 0.901304 0.004913 +features means NOUN 0.2375566671853132 0.888477 0.000266 +exposure losses NOUN 0.14674511245781166 0.819592 0.026247 +floor ground NOUN 0.16892125742478056 0.736652 0.016804 +exposure pain NOUN 0.20123516554808615 0.581873 0.026846 +energy increase NOUN 0.1534252611376862 0.834619 0.001765 +emperor moment NOUN 0.10336098627921302 0.899058 0.001219 +feet pages NOUN 0.23768640815653497 0.824855 0.002283 +elements physics NOUN 0.08629874995375143 0.879435 0.000541 +firm foundation NOUN 0.12008727803435408 0.890057 0.001969 +face half NOUN 0.10281033134858725 0.794992 0.000589 +facility harbor NOUN 0.029430353844228513 0.907645 0.002388 +element option NOUN 0.1879486288306605 0.845322 0.000575 +employees municipality NOUN 0.193261872749831 0.910720 0.000240 +energy oxygen NOUN 0.2502036525946724 0.812613 0.001972 +element feature NOUN 0.3050948543804169 0.886874 0.001121 +features ones NOUN 0.27067916268425896 0.891385 0.001029 +elections merger NOUN 0.150943450370973 0.844691 0.000175 +face maximum NOUN 0.17185553529148911 0.821797 0.001308 +facilities missile NOUN 0.07510919668064192 0.798278 0.024147 +end passage NOUN 0.13590091592924147 0.839880 0.004428 +fish names NOUN 0.13365449093215204 0.927941 0.000755 +electricity goods NOUN 0.1361637867166314 0.893857 0.000636 +end extension NOUN 0.23005321108052798 0.812988 0.002735 +feet level NOUN 0.3985567845008585 0.869160 0.005198 +facilities palace NOUN 0.10519406690543712 0.893351 0.001529 +energy noise NOUN 0.25030268575794423 0.807611 0.007194 +extension gas NOUN 0.16144754067554934 0.879992 0.001599 +extension increase NOUN 0.15859853202808022 0.788024 0.021895 +features guest NOUN 0.1474133716660963 0.905230 0.000745 +fleet guns NOUN 0.07048398211284392 0.809190 0.002426 +employees phone NOUN 0.07417699390390806 0.870780 0.002036 +flow output NOUN 0.1309721551809902 0.885047 0.007305 +fire force NOUN 0.07521900489290306 0.875589 0.001908 +fear involvement NOUN 0.17977905905344407 0.899780 0.003247 +fleet islands NOUN 0.3428472192044406 0.874112 0.001650 +fight opening NOUN 0.17969048709846974 0.691191 0.002261 +engines images NOUN 0.1449702131063067 0.878190 0.000384 +election laws NOUN 0.11725187069415596 0.820377 0.002870 +elements instance NOUN 0.2893065226529473 0.878770 0.001626 +file pair NOUN 0.11602824369886516 0.853695 0.006949 +elements instruction NOUN 0.1818121526812746 0.863706 0.001271 +figures parks NOUN 0.15624642543874145 0.809033 0.001387 +emphasis instance NOUN 0.13742272309289535 0.745216 0.002276 +figures industries NOUN 0.216127355592066 0.856213 0.000881 +face fear NOUN 0.13396417676706082 0.807812 0.000984 +fleet harbor NOUN 0.03915153332546847 0.795498 0.022364 +elements frame NOUN 0.12328400006324351 0.871104 0.000620 +face opinion NOUN 0.20041875444711832 0.857214 0.000174 +focus mission NOUN 0.22776078249164924 0.752178 0.043338 +fight note NOUN 0.17391446666331425 0.805352 0.003953 +exposure mainstream NOUN 0.1590172069063916 0.775263 0.019584 +employment justice NOUN 0.1008275922200821 0.927677 0.000449 +features groups NOUN 0.22758549840173992 0.859120 0.003074 +figures influence NOUN 0.32099014670574755 0.923810 0.002676 +files frame NOUN 0.11667631837843792 0.843750 0.002653 +enemy library NOUN 0.21460219181416892 0.914188 0.000541 +fiction foundation NOUN 0.4164612331732147 0.848011 0.003855 +employment insurance NOUN 0.14060406996065394 0.928261 0.000436 +electricity loss NOUN 0.16158010321783342 0.851020 0.002120 +fact laws NOUN 0.10537053836578572 0.860521 0.001647 +fire park NOUN 0.1599528276011923 0.739692 0.009809 +features material NOUN 0.2909369041004994 0.853230 0.003488 +extension 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0.2259714643672611 0.510672 0.000095 +equipment experiments NOUN 0.22633220503871515 0.524086 0.000070 +engineer official NOUN 0.12897065289432122 0.579928 0.000431 +flag level NOUN 0.13329874961071783 0.502508 0.000727 +flag model NOUN 0.13913324800108864 0.597235 0.000943 +episodes page NOUN 0.1284738867450413 0.561968 0.000443 +father hand NOUN 0.1092251155214519 0.498647 0.000401 +empire nation NOUN 0.1013999500891435 0.516336 0.000482 +farmers offices NOUN 0.18071404439412453 0.504404 0.001758 +environment philosophy NOUN 0.2606554528789091 0.528198 0.000928 +fan pitch NOUN 0.08599109652928212 0.611362 0.000762 +episodes games NOUN 0.29849836296884463 0.532799 0.000177 +energy exposure NOUN 0.237028972649236 0.519275 0.000133 +farm forest NOUN 0.2591878733683484 0.422907 0.008727 +electricity models NOUN 0.20810496784429675 0.542948 0.000211 +energy hydrogen NOUN 0.09722368476749439 0.500050 0.000031 +equation model NOUN 0.1286973228139615 0.521761 0.000288 +entrance facility NOUN 0.16805718065205508 0.578320 0.002376 +elements materials NOUN 0.23935816980050767 0.549208 0.000344 +fact orders NOUN 0.10049172760509154 0.616680 0.015398 +focus mechanism NOUN 0.19958051110762884 0.572100 0.005449 +fans legend NOUN 0.17167606157855123 0.536905 0.003570 +flights journey NOUN 0.14095788579644192 0.540749 0.001607 +equipment message NOUN 0.1550637175132183 0.541090 0.000172 +factor focus NOUN 0.18105170572119011 0.503555 0.006005 +employees maintenance NOUN 0.16703899606711878 0.521474 0.000408 +entertainment morning NOUN 0.08198343634989554 0.559772 0.000722 +elements guns NOUN 0.1072869107930979 0.544434 0.001170 +enemy personnel NOUN 0.13412707011742708 0.521286 0.000932 +employees friend NOUN 0.09191033700849136 0.535589 0.001092 +engines manufacturers NOUN 0.24764392266283694 0.514757 0.000314 +employees partnership NOUN 0.18011960294198223 0.524026 0.000038 +fame freedom NOUN 0.026022236367219242 0.574234 0.004641 +employment investment NOUN 0.17376393984565672 0.525583 0.000123 +election kingdom NOUN 0.19392107907571138 0.526790 0.000625 +farm horse NOUN 0.09426755268387339 0.529977 0.000861 +flow increase NOUN 0.20876247014265245 0.535364 0.008204 +flights lines NOUN 0.11201691574725256 0.586466 0.005679 +flights launch NOUN 0.1431173502350022 0.552966 0.003422 +enemy library NOUN 0.21460219181416892 0.540603 0.000411 +elements memory NOUN 0.18644282387306074 0.502254 0.001329 +entrance lake NOUN 0.13378401285024066 0.528670 0.000050 +element note NOUN 0.18871158098077984 0.548481 0.000787 +energy index NOUN 0.11629951031781624 0.521294 0.000869 +employees parent NOUN 0.1786730462777131 0.590607 0.000909 +entertainment folk NOUN 0.18684821309009514 0.518975 0.000469 +electricity employment NOUN 0.14840786749495666 0.502050 0.000439 +entry maximum NOUN 0.11706338639639698 0.589939 0.001698 +episode issue NOUN 0.24681373041756485 0.531770 0.000196 +fish markets NOUN 0.13013669895703164 0.573716 0.001040 +environment oil NOUN 0.13733258823623185 0.522422 0.002882 +farmers newspaper NOUN 0.30215700930258166 0.516113 0.005096 +era office NOUN 0.10004090001781937 0.534602 0.001457 +entry extension NOUN 0.14522432545451894 0.542668 0.001619 +explanation job NOUN 0.16136745570857702 0.574506 0.003124 +favor god NOUN 0.10621911913100793 0.541082 0.004118 +elements places NOUN 0.31569641129497567 0.541516 0.000345 +enemy guns NOUN 0.09463109926383746 0.537807 0.001385 +equipment networks NOUN 0.2541192759519827 0.505357 0.000071 +experiment missions NOUN 0.17489163025973614 0.552597 0.001948 +fame law NOUN 0.023812729040249357 0.529854 0.001273 +experiment incident NOUN 0.17146433862429372 0.504405 0.006917 +fact pair NOUN 0.09167418933403308 0.577255 0.014357 +emperor followers NOUN 0.09904448253925419 0.576796 0.002082 +engineer historian NOUN 0.1914073666179831 0.561134 0.001372 +element object NOUN 0.2262317827636071 0.521905 0.000358 +faculty medicine NOUN 0.16983063208940918 0.521326 0.001588 +employees facilities NOUN 0.22073195972022694 0.509062 0.000125 +engineer facility NOUN 0.12466684762656217 0.537237 0.000432 +elements feature NOUN 0.2737048601295641 0.564529 0.000199 +experiment phenomenon NOUN 0.17813287849899384 0.497797 0.003398 +faith identity NOUN 0.16022949401662143 0.566841 0.009224 +father friend NOUN 0.12423596652527442 0.590968 0.010340 +experiment information NOUN 0.17947560940575155 0.582583 0.005312 +entertainment movies NOUN 0.253889828870985 0.510775 0.000321 +elements list NOUN 0.1478787937583711 0.557305 0.002225 +employees fire NOUN 0.1330597959702655 0.511863 0.000056 +faith minority NOUN 0.12835339125808962 0.579274 0.003475 +end leg NOUN 0.12418326087253055 0.643015 0.005619 +floor home NOUN 0.1077656282745917 0.562262 0.003569 +energy physics NOUN 0.11661289885393565 0.527149 0.001061 +end location NOUN 0.14485040821332157 0.583625 0.002835 +floor grade NOUN 0.10561525249105619 0.490441 0.013024 +episodes periods NOUN 0.1350407520321207 0.568551 0.000150 +environment homes NOUN 0.18252471452554972 0.519231 0.000905 +fall incident NOUN 0.12528564063041409 0.559319 0.001842 +fashion patterns NOUN 0.2711382610416266 0.617388 0.005664 +flights hours NOUN 0.11672123211610516 0.562581 0.001312 +election merger NOUN 0.12924724632121334 0.564308 0.000970 +elections festival NOUN 0.2863457231874849 0.564978 0.000267 +flag league NOUN 0.07967370756306491 0.546174 0.009239 +employees governments NOUN 0.19658652640711355 0.530862 0.000610 +faith person NOUN 0.13338106081047058 0.532190 0.002332 +fans patients NOUN 0.23001422975088595 0.569469 0.003461 +employment expansion NOUN 0.15951184934852602 0.532739 0.000366 +fans fiction NOUN 0.08261851758382963 0.573460 0.006459 +experience philosophy NOUN 0.1741427813049605 0.540936 0.001681 +end parts NOUN 0.22183831343372276 0.565992 0.000866 +engineer guitarist NOUN 0.11101567089062382 0.580012 0.000382 +elements metal NOUN 0.1675526672924128 0.509167 0.000272 +entry image NOUN 0.15230401360669155 0.526358 0.000995 +engines items NOUN 0.12979364522487277 0.508308 0.000427 +faculty members NOUN 0.14680025580974523 0.526358 0.003639 +employment experience NOUN 0.19334037094480092 0.522636 0.000339 +experiment patterns NOUN 0.22937814459636052 0.536490 0.003005 +engineer manufacturers NOUN 0.11811815491009549 0.549094 0.000273 +favor household NOUN 0.10604820384746391 0.629530 0.011032 +fans passengers NOUN 0.1299080529212221 0.508856 0.002675 +elements organizations NOUN 0.22235731043931542 0.541090 0.001076 +era peace NOUN 0.11777428342610541 0.589279 0.000953 +entry expansion NOUN 0.18100505581045456 0.526253 0.000740 +fishing meat NOUN 0.09182855875006618 0.542977 0.004066 +episodes percent NOUN 0.25069606499299474 0.531438 0.000143 +fans places NOUN 0.18645104006283228 0.588837 0.006723 +father none NOUN 0.027328362822044146 0.621083 0.024043 +enemy heart NOUN 0.14622445734144296 0.534995 0.000019 +elements origins NOUN 0.2594467520334965 0.518897 0.000168 +equipment graphics NOUN 0.15164024297362352 0.502113 0.000424 +environment form NOUN 0.23263582944084668 0.567692 0.000122 +end junction NOUN 0.2360801387116204 0.566419 0.001739 +election idea NOUN 0.11775644452311852 0.534676 0.000268 +elements era NOUN 0.1668515019020081 0.535371 0.002698 diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wc-wordsi-order-scores-psd.dat.svn-base b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wc-wordsi-order-scores-psd.dat.svn-base new file mode 100644 index 00000000..7d97de5b --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wc-wordsi-order-scores-psd.dat.svn-base @@ -0,0 +1,3 @@ +# segment k-means-f k-means-v spec-f spec-v cbc-f cbc-v online-f online-v +0 0.0 0.0 0.0 0.792888172049 0.135158135901 +1 0.0 0.0 0.0 0.0 diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wc-wordsi-order-scores-ukwac.dat.svn-base b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wc-wordsi-order-scores-ukwac.dat.svn-base new file mode 100644 index 00000000..fbf9e6c0 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wc-wordsi-order-scores-ukwac.dat.svn-base @@ -0,0 +1,10 @@ +# segment k-means-f k-means-v spec-f spec-v cbc-f cbc-v online-f online-v +0 0.0 0.0 0.3341235648915307 0.126 0.05447024237792709 0.292 0.3506989243044264 0.128 +1 0.0 0.0 0.3556355498620261 0.121 0.05474561146191701 0.291 0.4050859742978117 0.123 +2 0.0 0.0 0.35085959064124883 0.127 0.05511596203050272 0.293 0.43949049102510024 0.121 +3 0.0 0.0 0.35563565327260765 0.121 0.056689761162537614 0.292 0.4397796895790214 0.115 +4 0.0 0.0 0.3599039240383986 0.118 0.05617020344917284 0.292 0.4534757375220293 0.117 +5 0.0 0.0 0.3788513303143586 0.119 0.053488138060633066 0.291 0.44664571736024705 0.106 +6 0.0 0.0 0.3605278439860727 0.116 0.11507153539264685 0.277 0.4575482363514336 0.109 +7 0.0 0.0 0.36536941549323104 0.113 0.11560391057296564 0.277 0.42624108509133607 0.115 +8 0.0 0.0 0.37814075300430916 0.117 0.11293494976359741 0.276 0.41448658559055057 0.12 diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wc-wordsi-order-scores-wiki.dat.svn-base b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wc-wordsi-order-scores-wiki.dat.svn-base new file mode 100644 index 00000000..a57a35c7 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wc-wordsi-order-scores-wiki.dat.svn-base @@ -0,0 +1,8 @@ +# segment k-means-f k-means-v spec-f spec-v cbc-f cbc-v online-f online-v +0 0.0 0.0 0.3396160497295356 0.126 0.052336957873767014 0.291 0.35186534608860826 0.136 +1 0.0 0.0 0.34866683909690516 0.126 0.05292552480214448 0.29 0.4049355631276 0.119 +2 0.0 0.0 0.35758825460933524 0.129 0.05154701787136734 0.293 0.42868928969842646 0.123 +3 0.0 0.0 0.34607586200081386 0.12 0.052980652513274905 0.293 0.4352392905685533 0.116 +4 0.0 0.0 0.3652853888338275 0.118 0.05399104039868371 0.295 0.4348690930211146 0.127 +5 0.0 0.0 0.3818834728998791 0.118 0.05181302004105827 0.293 0.4273392724149799 0.12 +6 0.0 0.0 0.38006315093528686 0.131 0.05243832541005984 0.294 0.42908898394780925 0.105 diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wc-wordsi-order-stkm.dat.svn-base b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wc-wordsi-order-stkm.dat.svn-base new file mode 100644 index 00000000..d1060b33 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wc-wordsi-order-stkm.dat.svn-base @@ -0,0 +1,1496 @@ +# term1 term2 pos simScore psdScore +empire journalist NOUN 0.1674908741062871 0.774294 0.001420 +form implementation NOUN 0.2790211481567622 0.851117 0.001167 +followers places NOUN 0.2531309063140091 0.829843 0.002812 +extension maintenance NOUN 0.1556574090782601 0.871084 0.001090 +facility municipality NOUN 0.11886795238546029 0.904624 0.003855 +elements physics NOUN 0.08629874995375143 0.634797 0.001036 +elements movements NOUN 0.285539826784524 0.577956 0.000238 +facilities girls NOUN 0.10945651827054301 0.790169 0.000836 +facilities library NOUN 0.22155357467457143 0.846716 0.005494 +exposure network NOUN 0.1887668892646738 0.792610 0.000672 +facility papers NOUN 0.1742452973367002 0.757033 0.003722 +elements jazz NOUN 0.16651618596463924 0.644569 0.000657 +followers heart NOUN 0.05336179057405993 0.836737 0.011010 +election laws NOUN 0.11725187069415596 0.590463 0.000370 +elements fans NOUN 0.1970242693583914 0.581489 0.000048 +extension harbor NOUN 0.030796848380403946 0.858729 0.003238 +form ones NOUN 0.29032298937850537 0.870428 0.001743 +forest palace NOUN 0.1084634382827927 0.880308 0.004445 +format manner NOUN 0.2563418795917451 0.944673 0.000530 +element orbit NOUN 0.09281926134157507 0.650275 0.000860 +extent height NOUN 0.11279104082778947 0.945429 0.000412 +extension heritage NOUN 0.10136104352361135 0.808628 0.004932 +elements pair NOUN 0.21294212330858336 0.670776 0.003727 +extension path NOUN 0.16970310922134405 0.828611 0.004015 +elections governments NOUN 0.35172332669746303 0.620341 0.000088 +face fear NOUN 0.13396417676706082 0.798998 0.006140 +format methods NOUN 0.24195448949558704 0.767898 0.005380 +elements influences NOUN 0.39877589324618257 0.603392 0.000872 +elections newspaper NOUN 0.17439810274448328 0.647648 0.000174 +emphasis numbers NOUN 0.14693902315096335 0.794044 0.000144 +form logic NOUN 0.15635282733080755 0.866179 0.001167 +facilities fishing NOUN 0.1666409870320078 0.811931 0.006465 +food mixture NOUN 0.18824308981084528 0.938632 0.000406 +elements movies NOUN 0.1580213740640297 0.594524 0.000332 +face foot NOUN 0.12221464224310036 0.816543 0.001698 +followers minutes NOUN 0.12313804380583247 0.798459 0.001848 +emphasis equipment NOUN 0.15237477015061437 0.799519 0.000059 +empire influences NOUN 0.08860677215760719 0.671426 0.000574 +explanation models NOUN 0.20454548079298257 0.640761 0.000487 +form music NOUN 0.24849432984419292 0.881091 0.001305 +elements movement NOUN 0.19028159133368325 0.605511 0.000040 +electricity equipment NOUN 0.18370524277440378 0.572454 0.000551 +facility force NOUN 0.13183452148280855 0.771912 0.006445 +format object NOUN 0.21928420902117243 0.804749 0.003546 +followers mother NOUN 0.2029269836568256 0.882671 0.001356 +emphasis features NOUN 0.17464429743527998 0.774757 0.000328 +facilities medium NOUN 0.17254698935054397 0.813138 0.004078 +form letter NOUN 0.15831082722144763 0.848546 0.001428 +form makeup NOUN 0.004835187983749416 0.981676 0.000444 +facilities goods NOUN 0.2028998024302152 0.733126 0.000765 +form input NOUN 0.14979760129555156 0.830011 0.001954 +election meetings NOUN 0.14456320526610175 0.627078 0.000719 +elements minutes NOUN 0.12541528114536105 0.640096 0.000146 +facilities methods NOUN 0.3321904016550174 0.741913 0.000449 +emphasis influences NOUN 0.17863638376384497 0.783556 0.000676 +facilities lack NOUN 0.17806114001563217 0.989387 0.000002 +extent increase NOUN 0.0708458905343281 0.892818 0.001137 +elements path NOUN 0.17835412549239754 0.582306 0.000865 +electricity flow NOUN 0.21381123176428066 0.613396 0.000326 +form identity NOUN 0.17731769305458117 0.795345 0.002480 +elements members NOUN 0.2254625530126927 0.601063 0.000084 +elements literature NOUN 0.22511426166985768 0.619248 0.000741 +facilities papers NOUN 0.16816818513730164 0.782017 0.000929 +elements philosophy NOUN 0.19339650939770636 0.594448 0.000500 +elements implementation NOUN 0.24683896930934232 0.612002 0.000116 +folk hall NOUN 0.14308417677523555 0.697115 0.001131 +element planet NOUN 0.13000560999113092 0.698497 0.002698 +elements ideas NOUN 0.4421058853668334 0.560321 0.000300 +empire influence NOUN 0.13875486324625483 0.648562 0.000623 +elections nomination NOUN 0.17094787447093726 0.672975 0.000447 +face god NOUN 0.16883893720410306 0.863941 0.001538 +elements index NOUN 0.09835958265770244 0.599396 0.001315 +face pitch NOUN 0.14170538967334556 0.828809 0.000751 +extension half NOUN 0.21539018905963084 0.921113 0.001071 +facilities materials NOUN 0.18780131065788871 0.762396 0.000321 +folk legend NOUN 0.15149960056576367 0.681258 0.000146 +form noise NOUN 0.15388697111063865 0.862826 0.005229 +empire nation NOUN 0.1013999500891435 0.604330 0.001624 +followers kingdom NOUN 0.21828815867192636 0.897777 0.003097 +emphasis form NOUN 0.14630093123629634 0.827669 0.000115 +food parent NOUN 0.08334303554451343 0.797462 0.004075 +elements medium NOUN 0.18071406933828324 0.632301 0.000200 +form names NOUN 0.31078467907643387 0.822030 0.001794 +facility phase NOUN 0.1649510379007541 0.809147 0.004882 +forces housing NOUN 0.01967323809423818 0.941465 0.000306 +form moment NOUN 0.13268268459180058 0.924426 0.000660 +format ideas NOUN 0.22585435092170103 0.803144 0.002759 +forest garden NOUN 0.12201232030621409 0.755777 0.002010 +folk 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0.562988 0.016090 +employment length NOUN 0.22747915456544554 0.537445 0.000184 +father mind NOUN 0.21246868842852953 0.546884 0.004425 +employees models NOUN 0.1954057866281818 0.515813 0.000041 +episode phase NOUN 0.2843957199926532 0.520877 0.000245 +forest hills NOUN 0.297514666635908 0.635062 0.008163 +father god NOUN 0.3182370907348626 0.516481 0.004547 +father job NOUN 0.20214111377408664 0.586438 0.004926 +fans inhabitants NOUN 0.19779725146415084 0.547648 0.008362 +forces housing NOUN 0.01967323809423818 0.685811 0.023543 +enemies historians NOUN 0.17211189687428144 0.520156 0.000074 +employees ministers NOUN 0.14708020821340498 0.533462 0.006598 +flights meetings NOUN 0.1188275491846177 0.544281 0.008486 +enemies existence NOUN 0.14880116378796773 0.536996 0.001404 +episode films NOUN 0.13433188733789114 0.556213 0.000292 +equipment gas NOUN 0.08998551786843123 0.534441 0.000188 +force links NOUN 0.07590788237076741 0.538932 0.006155 +error example NOUN 0.13832437632341388 0.505208 0.000068 +films motion NOUN 0.05956449950694212 0.632461 0.003889 +error material NOUN 0.14042149722998742 0.515230 0.000016 +element material NOUN 0.18366626909120085 0.514383 0.000220 +focus participants NOUN 0.19674884789331626 0.547484 0.005947 +elements novel NOUN 0.1873588730499334 0.560765 0.000812 +equation object NOUN 0.12764442594000017 0.502162 0.000145 +empire involvement NOUN 0.09749476986717312 0.534288 0.000173 +electricity generation NOUN 0.19544215820653488 0.510870 0.001012 +energy maximum NOUN 0.1789748647634415 0.526796 0.000085 +floor level NOUN 0.3741956521129916 0.607658 0.007596 +episodes match NOUN 0.1672617256053725 0.548232 0.000620 +enemy fire NOUN 0.14661134452343969 0.514168 0.000214 +father hands NOUN 0.16568796428821228 0.551949 0.005023 +forest ocean NOUN 0.07045555209102984 0.618428 0.009158 diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wc-wordsi-pos-scores-psd.dat.svn-base b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wc-wordsi-pos-scores-psd.dat.svn-base new file mode 100644 index 00000000..d12b0b53 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wc-wordsi-pos-scores-psd.dat.svn-base @@ -0,0 +1,3 @@ +# segment k-means-f k-means-v spec-f spec-v cbc-f cbc-v online-f online-v +0 0.0 0.0 0.0 0.763666415974 0.162927402837 +1 0.0 0.0 0.0 0.0 diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wc-wordsi-pos-scores-ukwac.dat.svn-base b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wc-wordsi-pos-scores-ukwac.dat.svn-base new file mode 100644 index 00000000..0298fd3d --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wc-wordsi-pos-scores-ukwac.dat.svn-base @@ -0,0 +1,10 @@ +# segment k-means-f k-means-v spec-f spec-v cbc-f cbc-v online-f online-v +0 0.2431711213335851 0.153 0.3402844339588588 0.125 0.1036635691771505 0.251 0.48850971938630755 0.084 +1 0.23552449038098608 0.149 0.3380714960333629 0.126 0.10074649312991905 0.253 0.48387042706626837 0.092 +2 0.23699993948868212 0.15 0.3523217457096568 0.133 0.09680002590775717 0.252 0.47335829769663573 0.087 +3 0.23730979051492695 0.155 0.0 0.0 0.09824911331572249 0.251 0.5185606659428239 0.08 +4 0.235207730039108 0.153 0.35603072603199176 0.124 0.1103241722335474 0.246 0.5225150349249517 0.075 +5 0.23842653887580406 0.155 0.3606392897727896 0.126 0.09604694462737454 0.252 0.5139181266341651 0.065 +6 0.27958186341455393 0.151 0.36729069593378705 0.124 0.15175081885516908 0.24 0.5405424684142343 0.072 +7 0.27947173873733105 0.152 0.3443403363443902 0.122 0.1501427013295703 0.241 0.5569251475675331 0.065 +8 0.27441784698936744 0.149 0.3581453008851822 0.126 0.1519614654288678 0.244 0.5694125452679483 0.059 diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wc-wordsi-pos-scores-wiki.dat.svn-base b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wc-wordsi-pos-scores-wiki.dat.svn-base new file mode 100644 index 00000000..04800bae --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wc-wordsi-pos-scores-wiki.dat.svn-base @@ -0,0 +1,8 @@ +# segment k-means-f k-means-v spec-f spec-v cbc-f cbc-v online-f online-v +0 0.24095882553280035 0.15 0.33615315539253193 0.127 0.10233679426802733 0.251 0.0 0.0 +1 0.23602802223253083 0.151 0.355702184383889 0.127 0.10063230242601535 0.252 0.4822465229287391 0.088 +2 0.23731750110449898 0.157 0.36283948286951195 0.127 0.11737528220270681 0.241 0.508006307979701 0.079 +3 0.23720772154428346 0.162 0.3413750625307264 0.13 0.11022341422239683 0.244 0.524770772536097 0.073 +4 0.23323617587127013 0.156 0.34983928159936833 0.127 0.07412956622825755 0.25 0.5189596580348228 0.072 +5 0.2361595377154521 0.161 0.3473391362060019 0.127 0.07544077838153962 0.248 0.5296109263845704 0.071 +6 0.23550548147984224 0.158 0.3298808913212924 0.129 0.0 0.0 0.524454031421209 0.064 diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wc-wordsi-pos-stkm.dat.svn-base b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wc-wordsi-pos-stkm.dat.svn-base new file mode 100644 index 00000000..295307e7 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wc-wordsi-pos-stkm.dat.svn-base @@ -0,0 +1,1990 @@ +# term1 term2 pos simScore psdScore +elements musician NOUN 0.13576388685271545 0.524754 0.000663 +employment firm NOUN 0.17810232693909825 0.520116 0.000042 +elements link NOUN 0.11931139166911299 0.524248 0.000172 +evening oil NOUN 0.09690155091635708 0.539670 0.000169 +employees fans NOUN 0.20588850005209988 0.516869 0.000190 +entrance features NOUN 0.1687379944810093 0.537945 0.000589 +entertainment motion NOUN 0.07769865442051532 0.506912 0.000039 +error mechanism NOUN 0.1313312528185631 0.522871 0.000292 +equation patient NOUN 0.08626194443060291 0.502463 0.000045 +energy methods NOUN 0.16902676135062356 0.514523 0.000143 +elements factor NOUN 0.24383644689636727 0.520240 0.000235 +era founder NOUN 0.1684077377885326 0.502655 0.000051 +engineer judge NOUN 0.1659320764138995 0.505609 0.000169 +equipment method NOUN 0.29472839580948273 0.591100 0.001384 +element object NOUN 0.2262317827636071 0.510777 0.000049 +equipment input NOUN 0.1529916411597461 0.520072 0.000473 +entertainment food NOUN 0.15365928190642542 0.516723 0.000058 +entrance lines NOUN 0.18908814343982686 0.551243 0.000419 +engineer manufacturers NOUN 0.11811815491009549 0.531478 0.000173 +employment exchange NOUN 0.11508768358990398 0.502404 0.000126 +employment independence NOUN 0.09880197117453317 0.520521 0.000195 +element ice NOUN 0.11042339218749835 0.515522 0.000080 +episodes hit NOUN 0.12467062528300556 0.526195 0.000084 +environment extension NOUN 0.19959061239721837 0.511814 0.000050 +entrance facility NOUN 0.16805718065205508 0.515864 0.000237 +environment future NOUN 0.09477499287902177 0.522026 0.000418 +environment ideas NOUN 0.231890407591558 0.512320 0.000123 +election morning NOUN 0.08538200174663337 0.510915 0.000071 +everything idea NOUN 0.17280943967733778 0.531576 0.001280 +elements experiments NOUN 0.24182865555999172 0.527655 0.000330 +employees followers NOUN 0.2556452468096391 0.524477 0.000223 +evolution phenomenon NOUN 0.29942463542605324 0.508821 0.000155 +example experiment NOUN 0.20703930189505798 0.521574 0.000335 +everyone face NOUN 0.10191067557605492 0.521282 0.000999 +era example NOUN 0.1502732553083854 0.512068 0.000018 +employment participants NOUN 0.18372458186634266 0.527612 0.002237 +employees jobs NOUN 0.31808817808347334 0.512810 0.000051 +employees operators NOUN 0.16442541011359815 0.499069 0.001547 +episode half NOUN 0.10446821036960666 0.505660 0.000011 +era facilities NOUN 0.14010445135656224 0.534402 0.001574 +example extent NOUN 0.08705477603422833 0.519079 0.000147 +equipment operations NOUN 0.3592387930430725 0.521430 0.000141 +emperor origin NOUN 0.09877826759751282 0.498896 0.000027 +error need NOUN 0.16457120585200882 0.541475 0.000415 +enemies names NOUN 0.20010874875912463 0.527594 0.000066 +employees passenger NOUN 0.15846256810141054 0.524119 0.000398 +evolution eye NOUN 0.20976239028359572 0.511022 0.000235 +example measure NOUN 0.2732028850375565 0.520618 0.000208 +era nation NOUN 0.16378356023371907 0.503408 0.000011 +everyone mother NOUN 0.1131965340025447 0.534695 0.000096 +episode novel NOUN 0.180727038838005 0.504758 0.000108 +example model NOUN 0.2593744257483791 0.539756 0.000587 +episodes guest NOUN 0.09474931793202791 0.512736 0.000060 +examples factor NOUN 0.1496482168355684 0.507114 0.000144 +entrance fame NOUN 0.16292807892744718 0.532592 0.000847 +elements form NOUN 0.3592526983398237 0.527318 0.000049 +entertainment performances NOUN 0.15369896146166745 0.512774 0.000191 +example ministers NOUN 0.10877004182152593 0.570786 0.006183 +equipment need NOUN 0.1499662487626942 0.551382 0.000327 +elements historians NOUN 0.16973125887729995 0.512180 0.000359 +everything followers NOUN 0.140246636104801 0.554131 0.000384 +elements heads NOUN 0.15871887237474894 0.516481 0.000048 +error injury NOUN 0.11501976976623765 0.510966 0.000073 +everything parents NOUN 0.1707205362581191 0.541312 0.000427 +electricity particles NOUN 0.10711080211839648 0.506823 0.000812 +employees homes NOUN 0.21072499977289277 0.529141 0.000017 +estate money NOUN 0.061645614881245335 0.534874 0.000168 +elements inspiration NOUN 0.12312691201706769 0.519001 0.000054 +engines methods NOUN 0.219180106950784 0.519568 0.000138 +entertainment fashion NOUN 0.15547845371897873 0.508963 0.000088 +empire nation NOUN 0.1013999500891435 0.506715 0.000030 +employees house NOUN 0.0736504331013937 0.529041 0.000453 +examples homes NOUN 0.14971825111059317 0.559920 0.001231 +equipment manufacturers NOUN 0.25624371661703327 0.516368 0.000375 +environment issues NOUN 0.2779919345351749 0.527397 0.000123 +enemies figures NOUN 0.26951815900928605 0.525013 0.000790 +everything half NOUN 0.12882701141015102 0.586497 0.000112 +environment models NOUN 0.241366213285572 0.516416 0.000362 +episodes month NOUN 0.23744446789056597 0.510770 0.000151 +elements piece NOUN 0.2198256154577843 0.521247 0.000094 +era movement NOUN 0.1866809963177609 0.504407 0.000016 +event horse NOUN 0.1089316590184849 0.521426 0.000202 +entry image NOUN 0.15230401360669155 0.513730 0.000019 +episode move NOUN 0.13225343175667134 0.507514 0.000121 +environment hotel NOUN 0.12606442724377817 0.511563 0.000411 +everything order NOUN 0.16246677793827435 0.536695 0.000597 +event hero NOUN 0.16530965908535922 0.511013 0.000091 +employees offices NOUN 0.24263268726342221 0.534241 0.000015 +engines houses NOUN 0.1359804423019911 0.548539 0.000595 +equipment mode NOUN 0.21788769323379445 0.531331 0.000018 +evening information NOUN 0.09171204313730864 0.532279 0.000512 +employees fire NOUN 0.1330597959702655 0.528481 0.000054 +equipment operators NOUN 0.260042050138309 0.526959 0.001061 +employees enemies NOUN 0.2259714643672611 0.529813 0.000429 +elements passage NOUN 0.17172624954105586 0.524273 0.000174 +episodes images NOUN 0.24005889190230562 0.524945 0.000070 +element issue NOUN 0.21557876448372393 0.517141 0.000567 +empire officials NOUN 0.10455196298528538 0.555711 0.001693 +everything failure NOUN 0.10317752890638827 0.546074 0.000096 +election match NOUN 0.1059438033271937 0.520581 0.000318 +equipment features NOUN 0.27204327868240513 0.516446 0.000169 +environment lives NOUN 0.11691341686698954 0.526031 0.000485 +evidence involvement NOUN 0.1655827600825391 0.516019 0.000491 +episodes personality NOUN 0.11435283992477792 0.528162 0.000320 +estate homes NOUN 0.0663312763068453 0.522627 0.000158 +employment maintenance NOUN 0.1575147713831669 0.511460 0.000064 +everyone move NOUN 0.13159079361026774 0.534602 0.000272 +entertainment industry NOUN 0.21500503024213152 0.510709 0.000327 +engines maintenance NOUN 0.12517828540544126 0.532119 0.000157 +employment interest NOUN 0.18417152287696004 0.507056 0.000048 +episodes goals NOUN 0.17929672520520704 0.517480 0.000375 +electricity method NOUN 0.14870891641478343 0.497896 0.000865 +equation meters NOUN 0.10557076091239105 0.578434 0.006535 +employment justice NOUN 0.1008275922200821 0.510067 0.000333 +estate hero NOUN 0.05776650133696429 0.517618 0.000206 +example object NOUN 0.21476990507713722 0.526453 0.000169 +equation map NOUN 0.17325478498866628 0.504930 0.000013 +engineer path NOUN 0.13204745768635645 0.524830 0.000252 +equation function NOUN 0.18950297355108242 0.502062 0.000007 +equipment experiments NOUN 0.22633220503871515 0.517276 0.000104 +elements links NOUN 0.16948329901495135 0.515583 0.000126 +episodes inches NOUN 0.32600412068468215 0.710374 0.009628 +enemy opponent NOUN 0.22662733773100432 0.515925 0.000040 +environment farmers NOUN 0.16026772921504367 0.517922 0.000149 +enemy force NOUN 0.15769158848319495 0.515331 0.000105 +employees leader NOUN 0.18656909690646417 0.561186 0.000940 +event performances NOUN 0.17280536514947126 0.533213 0.000230 +elements index NOUN 0.09835958265770244 0.474275 0.005218 +end heads NOUN 0.12909799020857562 0.556601 0.000572 +elements mathematics NOUN 0.11322455416627356 0.516430 0.000021 +engineer pilot NOUN 0.14101273444105344 0.502604 0.000085 +evolution extension NOUN 0.1477450573286738 0.508515 0.000038 +entry instance NOUN 0.18339446233048645 0.533514 0.000135 +end leg NOUN 0.12418326087253055 0.555980 0.000435 +energy milk NOUN 0.11670209706173991 0.481148 0.008227 +entrance influences NOUN 0.2068563646216945 0.552783 0.001027 +everything material NOUN 0.1516992128115459 0.513879 0.000238 +employment infrastructure NOUN 0.2136723849187945 0.513162 0.000006 +employees farm NOUN 0.16536927613025634 0.537684 0.000549 +equation level NOUN 0.09951978279561063 0.511574 0.000542 +electricity management NOUN 0.17704080861677596 0.522809 0.000712 +employment percentage NOUN 0.0943900210572705 0.513514 0.000224 +employment material NOUN 0.18329790087668255 0.516375 0.000148 +elections meetings NOUN 0.4230627810768916 0.519624 0.000313 +energy housing NOUN 0.02029501392605377 0.629404 0.009335 +enemies issues NOUN 0.27593956371134276 0.516439 0.000174 +environment industry NOUN 0.19011696457913305 0.510911 0.000176 +emphasis needs NOUN 0.1683590765618307 0.534054 0.001086 +elections hero NOUN 0.13607765400268862 0.519323 0.000246 +evolution numbers NOUN 0.16513872803812724 0.512587 0.000083 +everything model NOUN 0.13348581739289056 0.541120 0.000113 +error failure NOUN 0.09438353409708986 0.518878 0.000101 +element male NOUN 0.07189218982726521 0.512322 0.000219 +enemy equipment NOUN 0.1488773041817696 0.541813 0.000390 +employment membership NOUN 0.27477874474984415 0.501151 0.000125 +elements paintings NOUN 0.1879301287675249 0.509266 0.000071 +employment order NOUN 0.19980159346114107 0.518537 0.000503 +entertainment planet NOUN 0.19214945699807787 0.517525 0.000053 +elements memory NOUN 0.18644282387306074 0.520289 0.000414 +energy maintenance NOUN 0.17618695048823488 0.518574 0.000059 +equipment land NOUN 0.03961211602465938 0.516633 0.000670 +evening network NOUN 0.15761539578095712 0.509011 0.000018 +elements laws NOUN 0.22250288444105143 0.495290 0.000053 +energy meat NOUN 0.10609672426310114 0.510425 0.000073 +engineer officer NOUN 0.40055798512318375 0.508607 0.000117 +entry maximum NOUN 0.11706338639639698 0.542539 0.000495 +episode generation NOUN 0.13699236393149897 0.533253 0.000674 +engineer forces NOUN 0.15390548701398205 0.512764 0.000392 +energy justice NOUN 0.08567102901899001 0.522698 0.000232 +episode morning NOUN 0.09651551125159208 0.501603 0.000096 +environment means NOUN 0.2156985769922254 0.517528 0.000448 +equipment pictures NOUN 0.08079176914836092 0.508916 0.000069 +era makeup NOUN 0.004630651717565567 0.536429 0.001282 +evidence example 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+existence models NOUN 0.17258167225153032 0.522379 0.001351 +electricity food NOUN 0.3209372458343252 0.504410 0.000407 +elements goals NOUN 0.12872331608811788 0.517583 0.000121 +exchange industries NOUN 0.0803584365811318 0.550726 0.000241 +evidence material NOUN 0.24064922052174 0.577139 0.005350 +elections hero NOUN 0.13607765400268862 0.584101 0.000093 +enemies movement NOUN 0.20105224060470453 0.517390 0.000202 +episodes fall NOUN 0.10734916352971095 0.520746 0.000522 +example passage NOUN 0.23011245206397216 0.671378 0.008827 +element night NOUN 0.14269585319710718 0.537414 0.000245 +evolution philosophy NOUN 0.2046876760917494 0.588955 0.000645 +example painting NOUN 0.16138232479571418 0.584253 0.003557 +entry order NOUN 0.1558395773566272 0.571600 0.000847 +election membership NOUN 0.12068055562136003 0.535203 0.000052 +elements physics NOUN 0.08629874995375143 0.565845 0.001239 +event piece NOUN 0.19831513503816392 0.657652 0.004214 +episodes host NOUN 0.13226878364244393 0.517428 0.000069 +energy milk NOUN 0.11670209706173991 0.594800 0.005848 +event features NOUN 0.251694570343568 0.567933 0.006770 +end mouth NOUN 0.2823709850118857 0.540178 0.000059 +environment facilities NOUN 0.2384957179331461 0.521482 0.000032 +enemy missile NOUN 0.12119041185201446 0.524429 0.000421 +examples form NOUN 0.28585211291000834 0.564211 0.007642 +environment physics NOUN 0.09071904215083285 0.540974 0.000387 +equipment mode NOUN 0.21788769323379445 0.541542 0.000724 +experience partner NOUN 0.15349636611081144 0.513072 0.000164 +electricity output NOUN 0.15753697562637467 0.513084 0.000436 +entry example NOUN 0.13280059736774638 0.517383 0.000296 +energy index NOUN 0.11629951031781624 0.471698 0.006617 +everything humans NOUN 0.20779367019275072 0.598337 0.002799 +experience orders NOUN 0.19604411844574346 0.506016 0.000040 +example ideas NOUN 0.27864091982106826 0.595894 0.006686 +episode pair NOUN 0.1251002120932293 0.580661 0.000062 +element equation NOUN 0.10342959844202841 0.508749 0.000137 +element minute NOUN 0.3880072910706606 0.554178 0.000185 +elements location NOUN 0.17616546256359844 0.521090 0.000110 +engines mixture NOUN 0.1593978939013936 0.583633 0.000778 +electricity inspiration NOUN 0.11140797864287062 0.521400 0.000565 +end half NOUN 0.28243692512560176 0.540486 0.000343 +election move NOUN 0.09900892568025475 0.533654 0.000827 +elements names NOUN 0.3690149571423531 0.511385 0.000050 +emphasis limits NOUN 0.1729678788821776 0.651603 0.005511 +exchange markets NOUN 0.27101935772355645 0.519335 0.000111 +elections event NOUN 0.3081396785774584 0.524429 0.000293 +exception musicians NOUN 0.12908867374577596 0.560858 0.001131 +examples minutes NOUN 0.17855313473242793 0.593231 0.000221 +enemies exile NOUN 0.113945003613998 0.541015 0.000313 +environment index NOUN 0.12637532744662347 0.555148 0.008515 +exception influences NOUN 0.08611625471911626 0.551069 0.002238 +elements lines NOUN 0.21722051596731484 0.515255 0.000083 +employees hour NOUN 0.1134003228458366 0.517272 0.000026 +empire faith NOUN 0.09449427470045013 0.551769 0.000117 +episodes goals NOUN 0.17929672520520704 0.544125 0.000144 +examples incident NOUN 0.18879754958750228 0.598096 0.016537 +end hills NOUN 0.20963412310226123 0.552976 0.000103 +everyone existence NOUN 0.09660239875718098 0.552294 0.007218 +estate increase NOUN 0.0628856688887385 0.583258 0.006262 +everyone opponent NOUN 0.1005759528860639 0.593891 0.004845 +elements link NOUN 0.11931139166911299 0.518236 0.000332 +elections festival NOUN 0.2863457231874849 0.524029 0.000070 +existence image NOUN 0.16381709300556016 0.519190 0.000314 +expansion launch NOUN 0.11521967852382042 0.497698 0.000121 +environment land NOUN 0.042939099964224035 0.517988 0.000059 +existence images NOUN 0.14780873553531945 0.547039 0.000150 +expansion management NOUN 0.2484960390083635 0.537491 0.000495 +evidence example NOUN 0.17380259725383593 0.514821 0.007638 +examples exception NOUN 0.43806642264423135 0.605332 0.003355 +error need NOUN 0.16457120585200882 0.575436 0.007456 +episode novel NOUN 0.180727038838005 0.514074 0.000083 +experience inspiration NOUN 0.1321716428195592 0.570942 0.000262 +environment needs NOUN 0.19451772524598668 0.530236 0.000256 +employment facility NOUN 0.18273595306858223 0.517866 0.000082 +experience object NOUN 0.24041066644797035 0.511880 0.000292 +entry guard NOUN 0.09555201652738175 0.514781 0.004024 +equipment household NOUN 0.14392304041509402 0.686449 0.003916 +experience friend NOUN 0.11119313418045987 0.542322 0.000412 +equipment maintenance NOUN 0.2559752168522365 0.490088 0.000056 +element hits NOUN 0.11985605697967332 0.599539 0.000394 +episodes municipalities NOUN 0.24191394090791143 0.550336 0.000689 +electricity lines NOUN 0.15086248663168078 0.497226 0.000409 +electricity employment NOUN 0.14840786749495666 0.505126 0.000759 +elections officials NOUN 0.19021344588533293 0.556712 0.000274 +experience papers NOUN 0.18289601533053942 0.515127 0.000219 +examples figures NOUN 0.32908932185656353 0.493887 0.003079 +employment moon NOUN 0.2203058212679616 0.490704 0.001169 +entry facilities NOUN 0.14431540527280706 0.537321 0.000053 +employees member NOUN 0.19234834648373134 0.579011 0.000278 +enemies members NOUN 0.18313092390292912 0.513088 0.000054 +emphasis individual NOUN 0.14195473797522673 0.569997 0.000292 diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wc-wordsi-scores-psd.dat.svn-base b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wc-wordsi-scores-psd.dat.svn-base new file mode 100644 index 00000000..9a446721 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wc-wordsi-scores-psd.dat.svn-base @@ -0,0 +1,3 @@ +# segment k-means-f k-means-v spec-f spec-v cbc-f cbc-v online-f online-v +0 0.0 0.0 0.0 0.766361804509 0.161084197212 +1 0.0 0.0 0.0 0.0 diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wc-wordsi-scores-ukwac.dat.svn-base b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wc-wordsi-scores-ukwac.dat.svn-base new file mode 100644 index 00000000..876e7bdd --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wc-wordsi-scores-ukwac.dat.svn-base @@ -0,0 +1,10 @@ +# segment k-means-f k-means-v spec-f spec-v cbc-f cbc-v online-f online-v +0 0.24099680857254557 0.149 0.33012197281452627 0.125 0.1015589587957502 0.25 0.4939821600371211 0.099 +1 0.23959296089909907 0.154 0.34445680832989356 0.129 0.10126513905564176 0.253 0.47707522888267706 0.09 +2 0.24244901184355377 0.153 0.3489722543052073 0.126 0.09589274447949968 0.251 0.47896955681883496 0.088 +3 0.23573781024436427 0.154 0.35943480375957837 0.13 0.10333837612458834 0.246 0.522902794019169 0.079 +4 0.23932881538452871 0.152 0.365501529317694 0.129 0.09941509102656786 0.25 0.5188049495822099 0.075 +5 0.23599724637731714 0.152 0.35406103129853334 0.125 0.09615895270783849 0.251 0.5199286803301583 0.068 +6 0.2812854101855288 0.148 0.33949693594075514 0.126 0.15019087031129197 0.241 0.5554235549597045 0.071 +7 0.27518015270941026 0.149 0.3565564260327844 0.124 0.15222994117691352 0.242 0.5716979123864533 0.069 +8 0.2757061335636379 0.149 0.36227704514967163 0.13 0.15224581283316097 0.242 0.5684436969163075 0.058 diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wc-wordsi-scores-wiki.dat.svn-base b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wc-wordsi-scores-wiki.dat.svn-base new file mode 100644 index 00000000..fc23a3c8 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wc-wordsi-scores-wiki.dat.svn-base @@ -0,0 +1,8 @@ +# segment k-means-f k-means-v spec-f spec-v cbc-f cbc-v online-f online-v +0 0.2373555387627055 0.154 0.340509620167408 0.13 0.10351969075407183 0.251 0.0 0.0 +1 0.23645772392857003 0.152 0.3456903727119435 0.131 0.10127567655330828 0.254 0.47327079910143227 0.083 +2 0.24952328546651253 0.143 0.34515335586062884 0.126 0.11816759679697225 0.241 0.4748982298969292 0.09 +3 0.2395338380071576 0.159 0.3399282582981846 0.128 0.11127225075471205 0.243 0.5245567655954732 0.077 +4 0.23250032325993425 0.155 0.34909446183588916 0.125 0.10552098110090846 0.248 0.5188386058457585 0.075 +5 0.23295283393096874 0.156 0.35581519545080265 0.131 0.12642278745996777 0.239 0.5182819831155318 0.07 +6 0.23443258708238437 0.16 0.3337665092787791 0.123 0.0 0.0 0.5272215008591209 0.069 diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wc-wordsi-stkm.dat.svn-base b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wc-wordsi-stkm.dat.svn-base new file mode 100644 index 00000000..fcbedda7 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wc-wordsi-stkm.dat.svn-base @@ -0,0 +1,2977 @@ +# term1 term2 pos simScore psdScore +electricity models NOUN 0.20810496784429675 0.950185 0.000528 +form manner NOUN 0.1851047479963407 0.797773 0.048396 +evening newspapers NOUN 0.0932991082629685 0.856471 0.028160 +format mind NOUN 0.11827106092170471 0.879720 0.021878 +format image NOUN 0.298306741145858 0.954632 0.000312 +event fashion NOUN 0.15086971906638086 0.793490 0.040315 +fight loss NOUN 0.19749178333359527 0.869430 0.033415 +enemies organizations NOUN 0.1913118212728722 0.860451 0.028377 +episodes feet NOUN 0.29271959716115575 0.868690 0.022242 +element genus NOUN 0.13837368161931166 0.887331 0.032717 +everything failure NOUN 0.10317752890638827 0.956030 0.000075 +feature phenomenon NOUN 0.20567263349439072 0.985273 0.000080 +feet minutes NOUN 0.4833099095809491 0.859588 0.016281 +engineer parish NOUN 0.34030584080049703 0.959367 0.000358 +features industries NOUN 0.2723598444393853 0.932438 0.002672 +fight periods NOUN 0.1325840720930856 0.970741 0.000084 +elections festival NOUN 0.2863457231874849 0.976272 0.000070 +emperor empire NOUN 0.7297363915877593 0.875852 0.034187 +energy oxygen NOUN 0.2502036525946724 0.954054 0.000044 +estate functions NOUN 0.1008433449814665 0.940764 0.001407 +enemies issues NOUN 0.27593956371134276 0.954391 0.000290 +features object NOUN 0.2402946905627049 0.937688 0.001224 +foot limits NOUN 0.18730665455901216 0.952734 0.000380 +engines items NOUN 0.12979364522487277 0.768969 0.032736 +food insurance NOUN 0.14410230829700582 0.943226 0.000169 +form lead NOUN 0.1126755250636777 0.886885 0.033248 +features page NOUN 0.11926190859477839 0.948245 0.000335 +forest park NOUN 0.4383656906778442 0.964357 0.000150 +form ones NOUN 0.29032298937850537 0.968935 0.000041 +environment estate NOUN 0.05488344920365715 0.875050 0.033024 +features move NOUN 0.19254428911690505 0.876943 0.019615 +fight peace NOUN 0.09694486927344653 0.976854 0.000118 +fiction museum NOUN 0.21201057739121487 0.982772 0.000053 +employees feet NOUN 0.20118377335649373 0.951642 0.000611 +elements input NOUN 0.13378624469424436 0.967248 0.000159 +everything one NOUN 0.330283768201478 0.966125 0.000130 +features nations NOUN 0.14885811927159798 0.947959 0.000221 +form jurisdiction NOUN 0.23311899162686897 0.968628 0.000094 +equation instance NOUN 0.1570095065320288 0.796663 0.053991 +element issues NOUN 0.20276796292134758 0.952901 0.000297 +feature issues NOUN 0.15323467845532548 0.886006 0.026060 +emperor person NOUN 0.10407060390213521 0.968321 0.000100 +evidence past NOUN 0.14616030704863983 0.807796 0.043886 +examples homes NOUN 0.14971825111059317 0.794088 0.039981 +employment marriage NOUN 0.1338986031092246 0.894473 0.022370 +episodes pages NOUN 0.22446969050712795 0.954218 0.000530 +evening news NOUN 0.17038893779087935 0.783884 0.034896 +estate pair NOUN 0.05188157610974246 0.971360 0.000198 +fear need NOUN 0.4520789524410063 0.785557 0.049135 +focus object NOUN 0.22721635430409207 0.957114 0.000434 +element influences NOUN 0.2093023616642291 0.959712 0.000267 +fear pain NOUN 0.1836584222268164 0.954723 0.000271 +election fall NOUN 0.2456795003871713 0.505511 0.000021 +election move NOUN 0.09900892568025475 0.971454 0.000331 +error maximum NOUN 0.1306215085705911 0.970246 0.000351 +environment partner NOUN 0.15699151650824206 0.953039 0.000632 +enemies gas NOUN 0.23814359514604203 0.862725 0.023946 +environment farmers NOUN 0.16026772921504367 0.959652 0.000141 +environment medium NOUN 0.16566649100090322 0.783075 0.051909 +end parts NOUN 0.22183831343372276 0.969758 0.000054 +fight friends NOUN 0.1575557855404758 0.965452 0.000157 +employees fire NOUN 0.1330597959702655 0.863850 0.022703 +food participants NOUN 0.16302314168549994 0.868225 0.029363 +end farm NOUN 0.21722183648097212 0.966183 0.000137 +evidence explanation NOUN 0.23130563739484392 0.891483 0.015910 +election governor NOUN 0.18433610749256396 0.787924 0.052173 +everything hand NOUN 0.10187440807765867 0.967619 0.000030 +favor movement NOUN 0.11676393927690075 0.887208 0.036988 +employees governments NOUN 0.19658652640711355 0.955912 0.000326 +elements logic NOUN 0.17372669718212744 0.949684 0.000155 +elements industries NOUN 0.3320161048736374 0.763345 0.033159 +engineer operations NOUN 0.20585062181996025 0.960152 0.000196 +feet meters NOUN 0.8429028412444961 0.875663 0.008229 +example living NOUN 0.028744216797220404 0.905477 0.008139 +example passage NOUN 0.23011245206397216 0.888822 0.033868 +everything none NOUN 0.04109325956809943 0.858516 0.036377 +engines facilities NOUN 0.16522975809381957 0.916433 0.002082 +example past NOUN 0.20982610252113712 0.789057 0.053463 +fight incident NOUN 0.3247469812904211 0.880609 0.031985 +elements months NOUN 0.12075763684417469 0.856413 0.028017 +empire historian NOUN 0.3818021439339718 0.983462 0.000007 +entry launch NOUN 0.15129814068518913 0.853996 0.030402 +forests parks NOUN 0.1356670807929964 0.966657 0.000047 +elements model NOUN 0.2742957420720917 0.939986 0.001761 +engines lines NOUN 0.13197909979271175 0.884010 0.019529 +error images NOUN 0.1279804152497696 0.873084 0.023576 +element features NOUN 0.27558060994891687 0.886124 0.023389 +era makeup NOUN 0.004630651717565567 0.991793 0.000071 +example level NOUN 0.14226929094148202 0.988469 0.000037 +emperor exile NOUN 0.11057199933505674 0.696380 0.052696 +feature mode NOUN 0.1757678873790843 0.868856 0.032121 +element equation NOUN 0.10342959844202841 0.976971 0.000144 +engineer pilot NOUN 0.14101273444105344 0.955638 0.000404 +enemies head NOUN 0.11396105037232189 0.959900 0.000085 +feature performance NOUN 0.15282701471410115 0.963653 0.000170 +event performance NOUN 0.19579532299387217 0.890379 0.033862 +followers heart NOUN 0.05336179057405993 0.793193 0.049381 +enemy operations NOUN 0.16853358735746943 0.952929 0.000443 +energy length NOUN 0.16085141114736806 0.881811 0.020740 +folk performances NOUN 0.12127462743163613 0.957615 0.000028 +fight generation NOUN 0.23575704079044052 0.962548 0.000155 +era invasion NOUN 0.1370245521552249 0.878117 0.035357 +form medicine NOUN 0.14251446838249454 0.885405 0.035355 +equipment frequency NOUN 0.19357192826186642 0.884550 0.022608 +fight jobs NOUN 0.19540993315524777 0.971672 0.000576 +followers mark NOUN 0.21237790853979588 0.959159 0.000485 +feet hits NOUN 0.09548785108227759 0.880385 0.010662 +episode event NOUN 0.1494102309312742 0.959836 0.000107 +everything participants NOUN 0.18941449803578736 0.898186 0.010964 +example exception NOUN 0.2614222945607277 0.798057 0.053396 +episode half NOUN 0.10446821036960666 0.897726 0.031831 +form measures NOUN 0.2712571264836016 0.963104 0.000797 +example friend NOUN 0.17637863410910581 0.987285 0.000054 +environment kind NOUN 0.20037534052751993 0.888321 0.037711 +employees journalist NOUN 0.14974864545180974 0.948107 0.000087 +format implementation NOUN 0.19546048994231818 0.787767 0.044302 +episode inches NOUN 0.16092403398392396 0.925961 0.007580 +everything parents NOUN 0.1707205362581191 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0.489000 0.000523 diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wordsi-rel-scores-psd.dat.svn-base b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wordsi-rel-scores-psd.dat.svn-base new file mode 100644 index 00000000..62aca4bc --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wordsi-rel-scores-psd.dat.svn-base @@ -0,0 +1,3 @@ +# segment k-means-f k-means-v spec-f spec-v cbc-f cbc-v online-f online-v +0 0.0 0.0 0.0 0.78574117865 0.146213151022 +1 0.0 0.0 0.0 0.0 diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wordsi-rel-scores-ukwac.dat.svn-base b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wordsi-rel-scores-ukwac.dat.svn-base new file mode 100644 index 00000000..1c99f624 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wordsi-rel-scores-ukwac.dat.svn-base @@ -0,0 +1,10 @@ +# segment k-means-f k-means-v spec-f spec-v cbc-f cbc-v online-f online-v +0 0.6168499780410607 0.026 0.34996606612596187 0.099 0.5984541389113184 0.029 0.42070649483011785 0.114 +1 0.0 0.0 0.29446568434857573 0.105 0.5973192045364485 0.03 0.4263025118286027 0.111 +2 0.6182347644260046 0.025 0.3082838861560848 0.099 0.606680987526181 0.027 0.434622969048288 0.106 +3 0.6182347644260046 0.025 0.3209818083128649 0.102 0.6066643650021947 0.027 0.4396114017059777 0.102 +4 0.6182347644260046 0.025 0.30988367485974805 0.101 0.6064144576155893 0.027 0.4519521696665746 0.107 +5 0.6182347644260046 0.025 0.2879237096781659 0.112 0.6064327834936453 0.027 0.44665651473456414 0.102 +6 0.6182347644260046 0.025 0.3161541493892068 0.106 0.6066828466629944 0.027 0.4660530039787947 0.1 +7 0.6182347644260046 0.025 0.27736352962896393 0.111 0.6065503232083772 0.027 0.47925044999629635 0.103 +8 0.6182347644260046 0.025 0.30397945631565915 0.115 0.6065759122790711 0.027 0.47005051219811417 0.103 diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wordsi-rel-scores-wiki.dat.svn-base b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wordsi-rel-scores-wiki.dat.svn-base new file mode 100644 index 00000000..42c7dc06 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/psd_dat/.svn/text-base/dv-wordsi-rel-scores-wiki.dat.svn-base @@ -0,0 +1,8 @@ +# segment k-means-f k-means-v spec-f spec-v cbc-f cbc-v online-f online-v +0 0.6169394515247332 0.026 0.30006338867666854 0.107 0.5983334034535096 0.029 0.3696820597461022 0.12 +1 0.20259039529214476 0.151 0.2753280705046053 0.108 0.6064228314061885 0.027 0.4308630813292238 0.109 +2 0.2041852438710118 0.149 0.2904887178693322 0.111 0.606538536740226 0.027 0.428446487711971 0.105 +3 0.2000931627629596 0.149 0.26301834098561244 0.115 0.6065344824541671 0.027 0.4396338345765405 0.106 +4 0.20499087613779554 0.15 0.2943617929001189 0.107 0.6065847624057844 0.027 0.0 0.0 +5 0.6182347644260046 0.025 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a/papers/2011_emnlp_unsup_impact/figures/psd_dat/ResultsBinner.java b/papers/2011_emnlp_unsup_impact/figures/psd_dat/ResultsBinner.java new file mode 100644 index 00000000..9ac9002d --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/psd_dat/ResultsBinner.java @@ -0,0 +1,41 @@ +import java.io.*; +import java.util.*; + +import edu.ucla.sspace.common.Statistics; + +public class ResultsBinner { + + public static void main(String[] args) throws Exception { + if (args.length < 1) { + System.out.println("usage: RB input.dat output.dat"); + return; + } + + List[] scores = new List[100]; + for (int i = 0; i < scores.length; ++i) + scores[i] = new ArrayList(); + + BufferedReader br = new BufferedReader(new FileReader(args[0])); + br.readLine(); + for (String line = null; (line = br.readLine()) != null; ) { + String[] arr = line.split("\\s+"); + if (arr.length != 6 || line.startsWith("#")) + continue; + double similarity = Double.parseDouble(arr[3]); + double psdAcc = Double.parseDouble(arr[4]); + int bucket = (int)(similarity * 100); + scores[bucket].add(psdAcc); + } + br.close(); + + for (int i = 0; i < scores.length; ++i) { + List s = (List)(scores[i]); + if (s.size() > 0) { + double stderr = (s.size() > 1 ? Statistics.stderr(s) : 0); + System.out.println(i + " " + Statistics.mean(s) + " " + + stderr + " " + s.size()); + } + } + } + +} \ No newline at end of file diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/Stats.class b/papers/2011_emnlp_unsup_impact/figures/psd_dat/Stats.class new file mode 100644 index 00000000..31a63dbe Binary files /dev/null and b/papers/2011_emnlp_unsup_impact/figures/psd_dat/Stats.class differ diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/Stats.java b/papers/2011_emnlp_unsup_impact/figures/psd_dat/Stats.java new file mode 100644 index 00000000..91c98f15 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/psd_dat/Stats.java @@ -0,0 +1,29 @@ +import java.io.*; +import java.util.*; + +import edu.ucla.sspace.common.Statistics; +import edu.ucla.sspace.util.LineReader; + +public class Stats { + + public static void main(String[] args) { +// List[] points = new List[60]; +// for (int i = 0; i < points.length; ++i) +// points[i] = new ArrayList(); + List numPoints = new ArrayList(); + for (String file : args) { + for (String line : new LineReader(new File(file))) { + String[] arr = line.split("\\s+"); + int i = Integer.parseInt(arr[0]); + if (i <= 60) + numPoints.add(Integer.parseInt(arr[3])); + } + } + + System.out.printf("Mean number of points %f, median %d (stddev %f)%n", + Statistics.mean(numPoints), + Statistics.median(numPoints), + Statistics.stddev(numPoints)); + } + +} \ No newline at end of file diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/binned/.svn/all-wcprops b/papers/2011_emnlp_unsup_impact/figures/psd_dat/binned/.svn/all-wcprops new file mode 100644 index 00000000..db72a875 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/psd_dat/binned/.svn/all-wcprops @@ -0,0 +1,197 @@ +K 25 +svn:wc:ra_dav:version-url +V 60 +/depot/!svn/ver/801/papers/unsup_2011/figures/psd_dat/binned +END +dv-wc-wordsi-order-sc06.dat.binned.dat +K 25 +svn:wc:ra_dav:version-url +V 99 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0.003398 +faith identity NOUN 0.16022949401662143 0.566841 0.009224 +father friend NOUN 0.12423596652527442 0.590968 0.010340 +experiment information NOUN 0.17947560940575155 0.582583 0.005312 +entertainment movies NOUN 0.253889828870985 0.510775 0.000321 +elements list NOUN 0.1478787937583711 0.557305 0.002225 +employees fire NOUN 0.1330597959702655 0.511863 0.000056 +faith minority NOUN 0.12835339125808962 0.579274 0.003475 +end leg NOUN 0.12418326087253055 0.643015 0.005619 +floor home NOUN 0.1077656282745917 0.562262 0.003569 +energy physics NOUN 0.11661289885393565 0.527149 0.001061 +end location NOUN 0.14485040821332157 0.583625 0.002835 +floor grade NOUN 0.10561525249105619 0.490441 0.013024 +episodes periods NOUN 0.1350407520321207 0.568551 0.000150 +environment homes NOUN 0.18252471452554972 0.519231 0.000905 +fall incident NOUN 0.12528564063041409 0.559319 0.001842 +fashion patterns NOUN 0.2711382610416266 0.617388 0.005664 +flights hours NOUN 0.11672123211610516 0.562581 0.001312 +election merger NOUN 0.12924724632121334 0.564308 0.000970 +elections festival NOUN 0.2863457231874849 0.564978 0.000267 +flag league NOUN 0.07967370756306491 0.546174 0.009239 +employees governments NOUN 0.19658652640711355 0.530862 0.000610 +faith person NOUN 0.13338106081047058 0.532190 0.002332 +fans patients NOUN 0.23001422975088595 0.569469 0.003461 +employment expansion NOUN 0.15951184934852602 0.532739 0.000366 +fans fiction NOUN 0.08261851758382963 0.573460 0.006459 +experience philosophy NOUN 0.1741427813049605 0.540936 0.001681 +end parts NOUN 0.22183831343372276 0.565992 0.000866 +engineer guitarist NOUN 0.11101567089062382 0.580012 0.000382 +elements metal NOUN 0.1675526672924128 0.509167 0.000272 +entry image NOUN 0.15230401360669155 0.526358 0.000995 +engines items NOUN 0.12979364522487277 0.508308 0.000427 +faculty members NOUN 0.14680025580974523 0.526358 0.003639 +employment experience NOUN 0.19334037094480092 0.522636 0.000339 +experiment patterns NOUN 0.22937814459636052 0.536490 0.003005 +engineer manufacturers NOUN 0.11811815491009549 0.549094 0.000273 +favor household NOUN 0.10604820384746391 0.629530 0.011032 +fans passengers NOUN 0.1299080529212221 0.508856 0.002675 +elements organizations NOUN 0.22235731043931542 0.541090 0.001076 +era peace NOUN 0.11777428342610541 0.589279 0.000953 +entry expansion NOUN 0.18100505581045456 0.526253 0.000740 +fishing meat NOUN 0.09182855875006618 0.542977 0.004066 +episodes percent NOUN 0.25069606499299474 0.531438 0.000143 +fans places NOUN 0.18645104006283228 0.588837 0.006723 +father none NOUN 0.027328362822044146 0.621083 0.024043 +enemy heart NOUN 0.14622445734144296 0.534995 0.000019 +elements origins NOUN 0.2594467520334965 0.518897 0.000168 +equipment graphics NOUN 0.15164024297362352 0.502113 0.000424 +environment form NOUN 0.23263582944084668 0.567692 0.000122 +end junction NOUN 0.2360801387116204 0.566419 0.001739 +election idea NOUN 0.11775644452311852 0.534676 0.000268 +elements era NOUN 0.1668515019020081 0.535371 0.002698 diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wc-wordsi-order-scores-psd.dat b/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wc-wordsi-order-scores-psd.dat new file mode 100644 index 00000000..7d97de5b --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wc-wordsi-order-scores-psd.dat @@ -0,0 +1,3 @@ +# segment k-means-f k-means-v spec-f spec-v cbc-f cbc-v online-f online-v +0 0.0 0.0 0.0 0.792888172049 0.135158135901 +1 0.0 0.0 0.0 0.0 diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wc-wordsi-order-scores-ukwac.dat b/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wc-wordsi-order-scores-ukwac.dat new file mode 100644 index 00000000..fbf9e6c0 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wc-wordsi-order-scores-ukwac.dat @@ -0,0 +1,10 @@ +# segment k-means-f k-means-v spec-f spec-v cbc-f cbc-v online-f online-v +0 0.0 0.0 0.3341235648915307 0.126 0.05447024237792709 0.292 0.3506989243044264 0.128 +1 0.0 0.0 0.3556355498620261 0.121 0.05474561146191701 0.291 0.4050859742978117 0.123 +2 0.0 0.0 0.35085959064124883 0.127 0.05511596203050272 0.293 0.43949049102510024 0.121 +3 0.0 0.0 0.35563565327260765 0.121 0.056689761162537614 0.292 0.4397796895790214 0.115 +4 0.0 0.0 0.3599039240383986 0.118 0.05617020344917284 0.292 0.4534757375220293 0.117 +5 0.0 0.0 0.3788513303143586 0.119 0.053488138060633066 0.291 0.44664571736024705 0.106 +6 0.0 0.0 0.3605278439860727 0.116 0.11507153539264685 0.277 0.4575482363514336 0.109 +7 0.0 0.0 0.36536941549323104 0.113 0.11560391057296564 0.277 0.42624108509133607 0.115 +8 0.0 0.0 0.37814075300430916 0.117 0.11293494976359741 0.276 0.41448658559055057 0.12 diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wc-wordsi-order-scores-wiki.dat b/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wc-wordsi-order-scores-wiki.dat new file mode 100644 index 00000000..a57a35c7 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wc-wordsi-order-scores-wiki.dat @@ -0,0 +1,8 @@ +# segment k-means-f k-means-v spec-f spec-v cbc-f cbc-v online-f online-v +0 0.0 0.0 0.3396160497295356 0.126 0.052336957873767014 0.291 0.35186534608860826 0.136 +1 0.0 0.0 0.34866683909690516 0.126 0.05292552480214448 0.29 0.4049355631276 0.119 +2 0.0 0.0 0.35758825460933524 0.129 0.05154701787136734 0.293 0.42868928969842646 0.123 +3 0.0 0.0 0.34607586200081386 0.12 0.052980652513274905 0.293 0.4352392905685533 0.116 +4 0.0 0.0 0.3652853888338275 0.118 0.05399104039868371 0.295 0.4348690930211146 0.127 +5 0.0 0.0 0.3818834728998791 0.118 0.05181302004105827 0.293 0.4273392724149799 0.12 +6 0.0 0.0 0.38006315093528686 0.131 0.05243832541005984 0.294 0.42908898394780925 0.105 diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wc-wordsi-order-stkm.dat b/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wc-wordsi-order-stkm.dat new file mode 100644 index 00000000..d1060b33 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wc-wordsi-order-stkm.dat @@ -0,0 +1,1496 @@ +# term1 term2 pos simScore psdScore +empire journalist NOUN 0.1674908741062871 0.774294 0.001420 +form implementation NOUN 0.2790211481567622 0.851117 0.001167 +followers places NOUN 0.2531309063140091 0.829843 0.002812 +extension maintenance NOUN 0.1556574090782601 0.871084 0.001090 +facility municipality NOUN 0.11886795238546029 0.904624 0.003855 +elements physics NOUN 0.08629874995375143 0.634797 0.001036 +elements movements NOUN 0.285539826784524 0.577956 0.000238 +facilities girls NOUN 0.10945651827054301 0.790169 0.000836 +facilities library NOUN 0.22155357467457143 0.846716 0.005494 +exposure network NOUN 0.1887668892646738 0.792610 0.000672 +facility papers NOUN 0.1742452973367002 0.757033 0.003722 +elements jazz NOUN 0.16651618596463924 0.644569 0.000657 +followers heart NOUN 0.05336179057405993 0.836737 0.011010 +election laws NOUN 0.11725187069415596 0.590463 0.000370 +elements fans NOUN 0.1970242693583914 0.581489 0.000048 +extension harbor NOUN 0.030796848380403946 0.858729 0.003238 +form ones NOUN 0.29032298937850537 0.870428 0.001743 +forest palace NOUN 0.1084634382827927 0.880308 0.004445 +format manner NOUN 0.2563418795917451 0.944673 0.000530 +element orbit NOUN 0.09281926134157507 0.650275 0.000860 +extent height NOUN 0.11279104082778947 0.945429 0.000412 +extension heritage NOUN 0.10136104352361135 0.808628 0.004932 +elements pair NOUN 0.21294212330858336 0.670776 0.003727 +extension path NOUN 0.16970310922134405 0.828611 0.004015 +elections governments NOUN 0.35172332669746303 0.620341 0.000088 +face fear NOUN 0.13396417676706082 0.798998 0.006140 +format methods NOUN 0.24195448949558704 0.767898 0.005380 +elements influences NOUN 0.39877589324618257 0.603392 0.000872 +elections newspaper NOUN 0.17439810274448328 0.647648 0.000174 +emphasis numbers NOUN 0.14693902315096335 0.794044 0.000144 +form logic NOUN 0.15635282733080755 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NOUN 0.15831082722144763 0.848546 0.001428 +form makeup NOUN 0.004835187983749416 0.981676 0.000444 +facilities goods NOUN 0.2028998024302152 0.733126 0.000765 +form input NOUN 0.14979760129555156 0.830011 0.001954 +election meetings NOUN 0.14456320526610175 0.627078 0.000719 +elements minutes NOUN 0.12541528114536105 0.640096 0.000146 +facilities methods NOUN 0.3321904016550174 0.741913 0.000449 +emphasis influences NOUN 0.17863638376384497 0.783556 0.000676 +facilities lack NOUN 0.17806114001563217 0.989387 0.000002 +extent increase NOUN 0.0708458905343281 0.892818 0.001137 +elements path NOUN 0.17835412549239754 0.582306 0.000865 +electricity flow NOUN 0.21381123176428066 0.613396 0.000326 +form identity NOUN 0.17731769305458117 0.795345 0.002480 +elements members NOUN 0.2254625530126927 0.601063 0.000084 +elements literature NOUN 0.22511426166985768 0.619248 0.000741 +facilities papers NOUN 0.16816818513730164 0.782017 0.000929 +elements philosophy NOUN 0.19339650939770636 0.594448 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ocean NOUN 0.07045555209102984 0.618428 0.009158 diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wc-wordsi-pos-scores-psd.dat b/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wc-wordsi-pos-scores-psd.dat new file mode 100644 index 00000000..d12b0b53 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wc-wordsi-pos-scores-psd.dat @@ -0,0 +1,3 @@ +# segment k-means-f k-means-v spec-f spec-v cbc-f cbc-v online-f online-v +0 0.0 0.0 0.0 0.763666415974 0.162927402837 +1 0.0 0.0 0.0 0.0 diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wc-wordsi-pos-scores-ukwac.dat b/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wc-wordsi-pos-scores-ukwac.dat new file mode 100644 index 00000000..0298fd3d --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wc-wordsi-pos-scores-ukwac.dat @@ -0,0 +1,10 @@ +# segment k-means-f k-means-v spec-f spec-v cbc-f cbc-v online-f online-v +0 0.2431711213335851 0.153 0.3402844339588588 0.125 0.1036635691771505 0.251 0.48850971938630755 0.084 +1 0.23552449038098608 0.149 0.3380714960333629 0.126 0.10074649312991905 0.253 0.48387042706626837 0.092 +2 0.23699993948868212 0.15 0.3523217457096568 0.133 0.09680002590775717 0.252 0.47335829769663573 0.087 +3 0.23730979051492695 0.155 0.0 0.0 0.09824911331572249 0.251 0.5185606659428239 0.08 +4 0.235207730039108 0.153 0.35603072603199176 0.124 0.1103241722335474 0.246 0.5225150349249517 0.075 +5 0.23842653887580406 0.155 0.3606392897727896 0.126 0.09604694462737454 0.252 0.5139181266341651 0.065 +6 0.27958186341455393 0.151 0.36729069593378705 0.124 0.15175081885516908 0.24 0.5405424684142343 0.072 +7 0.27947173873733105 0.152 0.3443403363443902 0.122 0.1501427013295703 0.241 0.5569251475675331 0.065 +8 0.27441784698936744 0.149 0.3581453008851822 0.126 0.1519614654288678 0.244 0.5694125452679483 0.059 diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wc-wordsi-pos-scores-wiki.dat b/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wc-wordsi-pos-scores-wiki.dat new file mode 100644 index 00000000..04800bae --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wc-wordsi-pos-scores-wiki.dat @@ -0,0 +1,8 @@ +# segment k-means-f k-means-v spec-f spec-v cbc-f cbc-v online-f online-v +0 0.24095882553280035 0.15 0.33615315539253193 0.127 0.10233679426802733 0.251 0.0 0.0 +1 0.23602802223253083 0.151 0.355702184383889 0.127 0.10063230242601535 0.252 0.4822465229287391 0.088 +2 0.23731750110449898 0.157 0.36283948286951195 0.127 0.11737528220270681 0.241 0.508006307979701 0.079 +3 0.23720772154428346 0.162 0.3413750625307264 0.13 0.11022341422239683 0.244 0.524770772536097 0.073 +4 0.23323617587127013 0.156 0.34983928159936833 0.127 0.07412956622825755 0.25 0.5189596580348228 0.072 +5 0.2361595377154521 0.161 0.3473391362060019 0.127 0.07544077838153962 0.248 0.5296109263845704 0.071 +6 0.23550548147984224 0.158 0.3298808913212924 0.129 0.0 0.0 0.524454031421209 0.064 diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wc-wordsi-pos-stkm.dat b/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wc-wordsi-pos-stkm.dat new file mode 100644 index 00000000..295307e7 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wc-wordsi-pos-stkm.dat @@ -0,0 +1,1990 @@ +# term1 term2 pos simScore psdScore +elements musician NOUN 0.13576388685271545 0.524754 0.000663 +employment firm NOUN 0.17810232693909825 0.520116 0.000042 +elements link NOUN 0.11931139166911299 0.524248 0.000172 +evening oil NOUN 0.09690155091635708 0.539670 0.000169 +employees fans NOUN 0.20588850005209988 0.516869 0.000190 +entrance features NOUN 0.1687379944810093 0.537945 0.000589 +entertainment motion NOUN 0.07769865442051532 0.506912 0.000039 +error mechanism NOUN 0.1313312528185631 0.522871 0.000292 +equation patient NOUN 0.08626194443060291 0.502463 0.000045 +energy methods NOUN 0.16902676135062356 0.514523 0.000143 +elements factor NOUN 0.24383644689636727 0.520240 0.000235 +era founder NOUN 0.1684077377885326 0.502655 0.000051 +engineer judge NOUN 0.1659320764138995 0.505609 0.000169 +equipment method NOUN 0.29472839580948273 0.591100 0.001384 +element object NOUN 0.2262317827636071 0.510777 0.000049 +equipment input NOUN 0.1529916411597461 0.520072 0.000473 +entertainment food NOUN 0.15365928190642542 0.516723 0.000058 +entrance lines NOUN 0.18908814343982686 0.551243 0.000419 +engineer manufacturers NOUN 0.11811815491009549 0.531478 0.000173 +employment exchange NOUN 0.11508768358990398 0.502404 0.000126 +employment independence NOUN 0.09880197117453317 0.520521 0.000195 +element ice NOUN 0.11042339218749835 0.515522 0.000080 +episodes hit NOUN 0.12467062528300556 0.526195 0.000084 +environment extension NOUN 0.19959061239721837 0.511814 0.000050 +entrance facility NOUN 0.16805718065205508 0.515864 0.000237 +environment future NOUN 0.09477499287902177 0.522026 0.000418 +environment ideas NOUN 0.231890407591558 0.512320 0.000123 +election morning NOUN 0.08538200174663337 0.510915 0.000071 +everything idea NOUN 0.17280943967733778 0.531576 0.001280 +elements experiments NOUN 0.24182865555999172 0.527655 0.000330 +employees followers NOUN 0.2556452468096391 0.524477 0.000223 +evolution phenomenon NOUN 0.29942463542605324 0.508821 0.000155 +example experiment NOUN 0.20703930189505798 0.521574 0.000335 +everyone face NOUN 0.10191067557605492 0.521282 0.000999 +era example NOUN 0.1502732553083854 0.512068 0.000018 +employment participants NOUN 0.18372458186634266 0.527612 0.002237 +employees jobs NOUN 0.31808817808347334 0.512810 0.000051 +employees operators NOUN 0.16442541011359815 0.499069 0.001547 +episode half NOUN 0.10446821036960666 0.505660 0.000011 +era facilities NOUN 0.14010445135656224 0.534402 0.001574 +example extent NOUN 0.08705477603422833 0.519079 0.000147 +equipment operations NOUN 0.3592387930430725 0.521430 0.000141 +emperor origin NOUN 0.09877826759751282 0.498896 0.000027 +error need NOUN 0.16457120585200882 0.541475 0.000415 +enemies names NOUN 0.20010874875912463 0.527594 0.000066 +employees passenger NOUN 0.15846256810141054 0.524119 0.000398 +evolution eye NOUN 0.20976239028359572 0.511022 0.000235 +example measure NOUN 0.2732028850375565 0.520618 0.000208 +era nation NOUN 0.16378356023371907 0.503408 0.000011 +everyone mother NOUN 0.1131965340025447 0.534695 0.000096 +episode novel NOUN 0.180727038838005 0.504758 0.000108 +example model NOUN 0.2593744257483791 0.539756 0.000587 +episodes guest NOUN 0.09474931793202791 0.512736 0.000060 +examples factor NOUN 0.1496482168355684 0.507114 0.000144 +entrance fame NOUN 0.16292807892744718 0.532592 0.000847 +elements form NOUN 0.3592526983398237 0.527318 0.000049 +entertainment performances NOUN 0.15369896146166745 0.512774 0.000191 +example ministers NOUN 0.10877004182152593 0.570786 0.006183 +equipment need NOUN 0.1499662487626942 0.551382 0.000327 +elements historians NOUN 0.16973125887729995 0.512180 0.000359 +everything followers NOUN 0.140246636104801 0.554131 0.000384 +elements heads NOUN 0.15871887237474894 0.516481 0.000048 +error injury NOUN 0.11501976976623765 0.510966 0.000073 +everything parents NOUN 0.1707205362581191 0.541312 0.000427 +electricity particles NOUN 0.10711080211839648 0.506823 0.000812 +employees homes NOUN 0.21072499977289277 0.529141 0.000017 +estate money NOUN 0.061645614881245335 0.534874 0.000168 +elements inspiration NOUN 0.12312691201706769 0.519001 0.000054 +engines methods NOUN 0.219180106950784 0.519568 0.000138 +entertainment fashion NOUN 0.15547845371897873 0.508963 0.000088 +empire nation NOUN 0.1013999500891435 0.506715 0.000030 +employees house NOUN 0.0736504331013937 0.529041 0.000453 +examples homes NOUN 0.14971825111059317 0.559920 0.001231 +equipment manufacturers NOUN 0.25624371661703327 0.516368 0.000375 +environment issues NOUN 0.2779919345351749 0.527397 0.000123 +enemies figures NOUN 0.26951815900928605 0.525013 0.000790 +everything half NOUN 0.12882701141015102 0.586497 0.000112 +environment models NOUN 0.241366213285572 0.516416 0.000362 +episodes month NOUN 0.23744446789056597 0.510770 0.000151 +elements piece NOUN 0.2198256154577843 0.521247 0.000094 +era movement NOUN 0.1866809963177609 0.504407 0.000016 +event horse NOUN 0.1089316590184849 0.521426 0.000202 +entry image NOUN 0.15230401360669155 0.513730 0.000019 +episode move NOUN 0.13225343175667134 0.507514 0.000121 +environment hotel NOUN 0.12606442724377817 0.511563 0.000411 +everything order NOUN 0.16246677793827435 0.536695 0.000597 +event hero NOUN 0.16530965908535922 0.511013 0.000091 +employees offices NOUN 0.24263268726342221 0.534241 0.000015 +engines houses NOUN 0.1359804423019911 0.548539 0.000595 +equipment mode NOUN 0.21788769323379445 0.531331 0.000018 +evening information NOUN 0.09171204313730864 0.532279 0.000512 +employees fire NOUN 0.1330597959702655 0.528481 0.000054 +equipment operators NOUN 0.260042050138309 0.526959 0.001061 +employees enemies NOUN 0.2259714643672611 0.529813 0.000429 +elements passage NOUN 0.17172624954105586 0.524273 0.000174 +episodes images NOUN 0.24005889190230562 0.524945 0.000070 +element issue NOUN 0.21557876448372393 0.517141 0.000567 +empire officials NOUN 0.10455196298528538 0.555711 0.001693 +everything failure NOUN 0.10317752890638827 0.546074 0.000096 +election match NOUN 0.1059438033271937 0.520581 0.000318 +equipment features NOUN 0.27204327868240513 0.516446 0.000169 +environment lives NOUN 0.11691341686698954 0.526031 0.000485 +evidence involvement NOUN 0.1655827600825391 0.516019 0.000491 +episodes personality NOUN 0.11435283992477792 0.528162 0.000320 +estate homes NOUN 0.0663312763068453 0.522627 0.000158 +employment maintenance NOUN 0.1575147713831669 0.511460 0.000064 +everyone move NOUN 0.13159079361026774 0.534602 0.000272 +entertainment industry NOUN 0.21500503024213152 0.510709 0.000327 +engines maintenance NOUN 0.12517828540544126 0.532119 0.000157 +employment interest NOUN 0.18417152287696004 0.507056 0.000048 +episodes goals NOUN 0.17929672520520704 0.517480 0.000375 +electricity method NOUN 0.14870891641478343 0.497896 0.000865 +equation meters NOUN 0.10557076091239105 0.578434 0.006535 +employment justice NOUN 0.1008275922200821 0.510067 0.000333 +estate hero NOUN 0.05776650133696429 0.517618 0.000206 +example object NOUN 0.21476990507713722 0.526453 0.000169 +equation map NOUN 0.17325478498866628 0.504930 0.000013 +engineer path NOUN 0.13204745768635645 0.524830 0.000252 +equation function NOUN 0.18950297355108242 0.502062 0.000007 +equipment experiments NOUN 0.22633220503871515 0.517276 0.000104 +elements links NOUN 0.16948329901495135 0.515583 0.000126 +episodes inches NOUN 0.32600412068468215 0.710374 0.009628 +enemy opponent NOUN 0.22662733773100432 0.515925 0.000040 +environment farmers NOUN 0.16026772921504367 0.517922 0.000149 +enemy force NOUN 0.15769158848319495 0.515331 0.000105 +employees leader NOUN 0.18656909690646417 0.561186 0.000940 +event performances NOUN 0.17280536514947126 0.533213 0.000230 +elements index NOUN 0.09835958265770244 0.474275 0.005218 +end heads NOUN 0.12909799020857562 0.556601 0.000572 +elements mathematics NOUN 0.11322455416627356 0.516430 0.000021 +engineer pilot NOUN 0.14101273444105344 0.502604 0.000085 +evolution extension NOUN 0.1477450573286738 0.508515 0.000038 +entry instance NOUN 0.18339446233048645 0.533514 0.000135 +end leg NOUN 0.12418326087253055 0.555980 0.000435 +energy milk NOUN 0.11670209706173991 0.481148 0.008227 +entrance influences NOUN 0.2068563646216945 0.552783 0.001027 +everything material NOUN 0.1516992128115459 0.513879 0.000238 +employment infrastructure NOUN 0.2136723849187945 0.513162 0.000006 +employees farm NOUN 0.16536927613025634 0.537684 0.000549 +equation level NOUN 0.09951978279561063 0.511574 0.000542 +electricity management NOUN 0.17704080861677596 0.522809 0.000712 +employment percentage NOUN 0.0943900210572705 0.513514 0.000224 +employment material NOUN 0.18329790087668255 0.516375 0.000148 +elections meetings NOUN 0.4230627810768916 0.519624 0.000313 +energy housing NOUN 0.02029501392605377 0.629404 0.009335 +enemies issues NOUN 0.27593956371134276 0.516439 0.000174 +environment industry NOUN 0.19011696457913305 0.510911 0.000176 +emphasis needs NOUN 0.1683590765618307 0.534054 0.001086 +elections hero NOUN 0.13607765400268862 0.519323 0.000246 +evolution numbers NOUN 0.16513872803812724 0.512587 0.000083 +everything model NOUN 0.13348581739289056 0.541120 0.000113 +error failure NOUN 0.09438353409708986 0.518878 0.000101 +element male NOUN 0.07189218982726521 0.512322 0.000219 +enemy equipment NOUN 0.1488773041817696 0.541813 0.000390 +employment membership NOUN 0.27477874474984415 0.501151 0.000125 +elements paintings NOUN 0.1879301287675249 0.509266 0.000071 +employment order NOUN 0.19980159346114107 0.518537 0.000503 +entertainment planet NOUN 0.19214945699807787 0.517525 0.000053 +elements memory NOUN 0.18644282387306074 0.520289 0.000414 +energy maintenance NOUN 0.17618695048823488 0.518574 0.000059 +equipment land NOUN 0.03961211602465938 0.516633 0.000670 +evening network NOUN 0.15761539578095712 0.509011 0.000018 +elements laws NOUN 0.22250288444105143 0.495290 0.000053 +energy meat NOUN 0.10609672426310114 0.510425 0.000073 +engineer officer NOUN 0.40055798512318375 0.508607 0.000117 +entry maximum NOUN 0.11706338639639698 0.542539 0.000495 +episode generation NOUN 0.13699236393149897 0.533253 0.000674 +engineer forces NOUN 0.15390548701398205 0.512764 0.000392 +energy justice NOUN 0.08567102901899001 0.522698 0.000232 +episode morning NOUN 0.09651551125159208 0.501603 0.000096 +environment means NOUN 0.2156985769922254 0.517528 0.000448 +equipment pictures NOUN 0.08079176914836092 0.508916 0.000069 +era makeup NOUN 0.004630651717565567 0.536429 0.001282 +evidence example NOUN 0.17380259725383593 0.532946 0.000464 +environment form NOUN 0.23263582944084668 0.505261 0.000108 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0.13598045233177583 0.522074 0.000244 +examples genus NOUN 0.11688128565248228 0.509865 0.000014 +evening paper NOUN 0.09216532289278018 0.523276 0.000359 +elements films NOUN 0.21887827409586316 0.510382 0.000128 +environment phenomenon NOUN 0.33565902779701834 0.509717 0.000107 +example explanation NOUN 0.2687428253484372 0.522846 0.000085 +everyone patient NOUN 0.1698196484115045 0.542268 0.000407 +enemies faith NOUN 0.1269326892929239 0.509831 0.000013 +end north NOUN 0.34142402306151703 0.501501 0.000013 +equipment maps NOUN 0.17361054961100164 0.519330 0.000323 +equipment material NOUN 0.2648906038021046 0.520737 0.000031 +equipment fire NOUN 0.15917586216534477 0.529135 0.000608 +election jurisdiction NOUN 0.2215439356257436 0.511320 0.000019 +event factor NOUN 0.23001279037148187 0.510515 0.000197 +era jazz NOUN 0.14560218523927632 0.521203 0.000548 +enemies planet NOUN 0.14144569347979452 0.538539 0.000381 +electricity lines NOUN 0.15086248663168078 0.506369 0.000475 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NOUN 0.11140797864287062 0.521400 0.000565 +end half NOUN 0.28243692512560176 0.540486 0.000343 +election move NOUN 0.09900892568025475 0.533654 0.000827 +elements names NOUN 0.3690149571423531 0.511385 0.000050 +emphasis limits NOUN 0.1729678788821776 0.651603 0.005511 +exchange markets NOUN 0.27101935772355645 0.519335 0.000111 +elections event NOUN 0.3081396785774584 0.524429 0.000293 +exception musicians NOUN 0.12908867374577596 0.560858 0.001131 +examples minutes NOUN 0.17855313473242793 0.593231 0.000221 +enemies exile NOUN 0.113945003613998 0.541015 0.000313 +environment index NOUN 0.12637532744662347 0.555148 0.008515 +exception influences NOUN 0.08611625471911626 0.551069 0.002238 +elements lines NOUN 0.21722051596731484 0.515255 0.000083 +employees hour NOUN 0.1134003228458366 0.517272 0.000026 +empire faith NOUN 0.09449427470045013 0.551769 0.000117 +episodes goals NOUN 0.17929672520520704 0.544125 0.000144 +examples incident NOUN 0.18879754958750228 0.598096 0.016537 +end hills NOUN 0.20963412310226123 0.552976 0.000103 +everyone existence NOUN 0.09660239875718098 0.552294 0.007218 +estate increase NOUN 0.0628856688887385 0.583258 0.006262 +everyone opponent NOUN 0.1005759528860639 0.593891 0.004845 +elements link NOUN 0.11931139166911299 0.518236 0.000332 +elections festival NOUN 0.2863457231874849 0.524029 0.000070 +existence image NOUN 0.16381709300556016 0.519190 0.000314 +expansion launch NOUN 0.11521967852382042 0.497698 0.000121 +environment land NOUN 0.042939099964224035 0.517988 0.000059 +existence images NOUN 0.14780873553531945 0.547039 0.000150 +expansion management NOUN 0.2484960390083635 0.537491 0.000495 +evidence example NOUN 0.17380259725383593 0.514821 0.007638 +examples exception NOUN 0.43806642264423135 0.605332 0.003355 +error need NOUN 0.16457120585200882 0.575436 0.007456 +episode novel NOUN 0.180727038838005 0.514074 0.000083 +experience inspiration NOUN 0.1321716428195592 0.570942 0.000262 +environment needs NOUN 0.19451772524598668 0.530236 0.000256 +employment facility NOUN 0.18273595306858223 0.517866 0.000082 +experience object NOUN 0.24041066644797035 0.511880 0.000292 +entry guard NOUN 0.09555201652738175 0.514781 0.004024 +equipment household NOUN 0.14392304041509402 0.686449 0.003916 +experience friend NOUN 0.11119313418045987 0.542322 0.000412 +equipment maintenance NOUN 0.2559752168522365 0.490088 0.000056 +element hits NOUN 0.11985605697967332 0.599539 0.000394 +episodes municipalities NOUN 0.24191394090791143 0.550336 0.000689 +electricity lines NOUN 0.15086248663168078 0.497226 0.000409 +electricity employment NOUN 0.14840786749495666 0.505126 0.000759 +elections officials NOUN 0.19021344588533293 0.556712 0.000274 +experience papers NOUN 0.18289601533053942 0.515127 0.000219 +examples figures NOUN 0.32908932185656353 0.493887 0.003079 +employment moon NOUN 0.2203058212679616 0.490704 0.001169 +entry facilities NOUN 0.14431540527280706 0.537321 0.000053 +employees member NOUN 0.19234834648373134 0.579011 0.000278 +enemies members NOUN 0.18313092390292912 0.513088 0.000054 +emphasis individual NOUN 0.14195473797522673 0.569997 0.000292 diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wc-wordsi-scores-psd.dat b/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wc-wordsi-scores-psd.dat new file mode 100644 index 00000000..9a446721 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wc-wordsi-scores-psd.dat @@ -0,0 +1,3 @@ +# segment k-means-f k-means-v spec-f spec-v cbc-f cbc-v online-f online-v +0 0.0 0.0 0.0 0.766361804509 0.161084197212 +1 0.0 0.0 0.0 0.0 diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wc-wordsi-scores-ukwac.dat b/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wc-wordsi-scores-ukwac.dat new file mode 100644 index 00000000..876e7bdd --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wc-wordsi-scores-ukwac.dat @@ -0,0 +1,10 @@ +# segment k-means-f k-means-v spec-f spec-v cbc-f cbc-v online-f online-v +0 0.24099680857254557 0.149 0.33012197281452627 0.125 0.1015589587957502 0.25 0.4939821600371211 0.099 +1 0.23959296089909907 0.154 0.34445680832989356 0.129 0.10126513905564176 0.253 0.47707522888267706 0.09 +2 0.24244901184355377 0.153 0.3489722543052073 0.126 0.09589274447949968 0.251 0.47896955681883496 0.088 +3 0.23573781024436427 0.154 0.35943480375957837 0.13 0.10333837612458834 0.246 0.522902794019169 0.079 +4 0.23932881538452871 0.152 0.365501529317694 0.129 0.09941509102656786 0.25 0.5188049495822099 0.075 +5 0.23599724637731714 0.152 0.35406103129853334 0.125 0.09615895270783849 0.251 0.5199286803301583 0.068 +6 0.2812854101855288 0.148 0.33949693594075514 0.126 0.15019087031129197 0.241 0.5554235549597045 0.071 +7 0.27518015270941026 0.149 0.3565564260327844 0.124 0.15222994117691352 0.242 0.5716979123864533 0.069 +8 0.2757061335636379 0.149 0.36227704514967163 0.13 0.15224581283316097 0.242 0.5684436969163075 0.058 diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wc-wordsi-scores-wiki.dat b/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wc-wordsi-scores-wiki.dat new file mode 100644 index 00000000..fc23a3c8 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wc-wordsi-scores-wiki.dat @@ -0,0 +1,8 @@ +# segment k-means-f k-means-v spec-f spec-v cbc-f cbc-v online-f online-v +0 0.2373555387627055 0.154 0.340509620167408 0.13 0.10351969075407183 0.251 0.0 0.0 +1 0.23645772392857003 0.152 0.3456903727119435 0.131 0.10127567655330828 0.254 0.47327079910143227 0.083 +2 0.24952328546651253 0.143 0.34515335586062884 0.126 0.11816759679697225 0.241 0.4748982298969292 0.09 +3 0.2395338380071576 0.159 0.3399282582981846 0.128 0.11127225075471205 0.243 0.5245567655954732 0.077 +4 0.23250032325993425 0.155 0.34909446183588916 0.125 0.10552098110090846 0.248 0.5188386058457585 0.075 +5 0.23295283393096874 0.156 0.35581519545080265 0.131 0.12642278745996777 0.239 0.5182819831155318 0.07 +6 0.23443258708238437 0.16 0.3337665092787791 0.123 0.0 0.0 0.5272215008591209 0.069 diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wc-wordsi-stkm.dat b/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wc-wordsi-stkm.dat new file mode 100644 index 00000000..fcbedda7 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wc-wordsi-stkm.dat @@ -0,0 +1,2977 @@ +# term1 term2 pos simScore psdScore +electricity models NOUN 0.20810496784429675 0.950185 0.000528 +form manner NOUN 0.1851047479963407 0.797773 0.048396 +evening newspapers NOUN 0.0932991082629685 0.856471 0.028160 +format mind NOUN 0.11827106092170471 0.879720 0.021878 +format image NOUN 0.298306741145858 0.954632 0.000312 +event fashion NOUN 0.15086971906638086 0.793490 0.040315 +fight loss NOUN 0.19749178333359527 0.869430 0.033415 +enemies organizations NOUN 0.1913118212728722 0.860451 0.028377 +episodes feet NOUN 0.29271959716115575 0.868690 0.022242 +element genus NOUN 0.13837368161931166 0.887331 0.032717 +everything failure NOUN 0.10317752890638827 0.956030 0.000075 +feature phenomenon NOUN 0.20567263349439072 0.985273 0.000080 +feet minutes NOUN 0.4833099095809491 0.859588 0.016281 +engineer parish NOUN 0.34030584080049703 0.959367 0.000358 +features industries NOUN 0.2723598444393853 0.932438 0.002672 +fight periods NOUN 0.1325840720930856 0.970741 0.000084 +elections festival NOUN 0.2863457231874849 0.976272 0.000070 +emperor empire NOUN 0.7297363915877593 0.875852 0.034187 +energy oxygen NOUN 0.2502036525946724 0.954054 0.000044 +estate functions NOUN 0.1008433449814665 0.940764 0.001407 +enemies issues NOUN 0.27593956371134276 0.954391 0.000290 +features object NOUN 0.2402946905627049 0.937688 0.001224 +foot limits NOUN 0.18730665455901216 0.952734 0.000380 +engines items NOUN 0.12979364522487277 0.768969 0.032736 +food insurance NOUN 0.14410230829700582 0.943226 0.000169 +form lead NOUN 0.1126755250636777 0.886885 0.033248 +features page NOUN 0.11926190859477839 0.948245 0.000335 +forest park NOUN 0.4383656906778442 0.964357 0.000150 +form ones NOUN 0.29032298937850537 0.968935 0.000041 +environment estate NOUN 0.05488344920365715 0.875050 0.033024 +features move NOUN 0.19254428911690505 0.876943 0.019615 +fight peace NOUN 0.09694486927344653 0.976854 0.000118 +fiction museum NOUN 0.21201057739121487 0.982772 0.000053 +employees feet NOUN 0.20118377335649373 0.951642 0.000611 +elements input NOUN 0.13378624469424436 0.967248 0.000159 +everything one NOUN 0.330283768201478 0.966125 0.000130 +features nations NOUN 0.14885811927159798 0.947959 0.000221 +form jurisdiction NOUN 0.23311899162686897 0.968628 0.000094 +equation instance NOUN 0.1570095065320288 0.796663 0.053991 +element issues NOUN 0.20276796292134758 0.952901 0.000297 +feature issues NOUN 0.15323467845532548 0.886006 0.026060 +emperor person NOUN 0.10407060390213521 0.968321 0.000100 +evidence past NOUN 0.14616030704863983 0.807796 0.043886 +examples homes NOUN 0.14971825111059317 0.794088 0.039981 +employment marriage NOUN 0.1338986031092246 0.894473 0.022370 +episodes pages NOUN 0.22446969050712795 0.954218 0.000530 +evening news NOUN 0.17038893779087935 0.783884 0.034896 +estate pair NOUN 0.05188157610974246 0.971360 0.000198 +fear need NOUN 0.4520789524410063 0.785557 0.049135 +focus object NOUN 0.22721635430409207 0.957114 0.000434 +element influences NOUN 0.2093023616642291 0.959712 0.000267 +fear pain NOUN 0.1836584222268164 0.954723 0.000271 +election fall NOUN 0.2456795003871713 0.505511 0.000021 +election move NOUN 0.09900892568025475 0.971454 0.000331 +error maximum NOUN 0.1306215085705911 0.970246 0.000351 +environment partner NOUN 0.15699151650824206 0.953039 0.000632 +enemies gas NOUN 0.23814359514604203 0.862725 0.023946 +environment farmers NOUN 0.16026772921504367 0.959652 0.000141 +environment medium NOUN 0.16566649100090322 0.783075 0.051909 +end parts NOUN 0.22183831343372276 0.969758 0.000054 +fight friends NOUN 0.1575557855404758 0.965452 0.000157 +employees fire NOUN 0.1330597959702655 0.863850 0.022703 +food participants NOUN 0.16302314168549994 0.868225 0.029363 +end farm NOUN 0.21722183648097212 0.966183 0.000137 +evidence explanation NOUN 0.23130563739484392 0.891483 0.015910 +election governor NOUN 0.18433610749256396 0.787924 0.052173 +everything hand NOUN 0.10187440807765867 0.967619 0.000030 +favor movement NOUN 0.11676393927690075 0.887208 0.036988 +employees governments NOUN 0.19658652640711355 0.955912 0.000326 +elements logic NOUN 0.17372669718212744 0.949684 0.000155 +elements industries NOUN 0.3320161048736374 0.763345 0.033159 +engineer operations NOUN 0.20585062181996025 0.960152 0.000196 +feet meters NOUN 0.8429028412444961 0.875663 0.008229 +example living NOUN 0.028744216797220404 0.905477 0.008139 +example passage NOUN 0.23011245206397216 0.888822 0.033868 +everything none NOUN 0.04109325956809943 0.858516 0.036377 +engines facilities NOUN 0.16522975809381957 0.916433 0.002082 +example past NOUN 0.20982610252113712 0.789057 0.053463 +fight incident NOUN 0.3247469812904211 0.880609 0.031985 +elements months NOUN 0.12075763684417469 0.856413 0.028017 +empire historian NOUN 0.3818021439339718 0.983462 0.000007 +entry launch NOUN 0.15129814068518913 0.853996 0.030402 +forests parks NOUN 0.1356670807929964 0.966657 0.000047 +elements model NOUN 0.2742957420720917 0.939986 0.001761 +engines lines NOUN 0.13197909979271175 0.884010 0.019529 +error images NOUN 0.1279804152497696 0.873084 0.023576 +element features NOUN 0.27558060994891687 0.886124 0.023389 +era makeup NOUN 0.004630651717565567 0.991793 0.000071 +example level NOUN 0.14226929094148202 0.988469 0.000037 +emperor exile NOUN 0.11057199933505674 0.696380 0.052696 +feature mode NOUN 0.1757678873790843 0.868856 0.032121 +element equation NOUN 0.10342959844202841 0.976971 0.000144 +engineer pilot NOUN 0.14101273444105344 0.955638 0.000404 +enemies head NOUN 0.11396105037232189 0.959900 0.000085 +feature performance NOUN 0.15282701471410115 0.963653 0.000170 +event performance NOUN 0.19579532299387217 0.890379 0.033862 +followers heart NOUN 0.05336179057405993 0.793193 0.049381 +enemy operations NOUN 0.16853358735746943 0.952929 0.000443 +energy length NOUN 0.16085141114736806 0.881811 0.020740 +folk performances NOUN 0.12127462743163613 0.957615 0.000028 +fight generation NOUN 0.23575704079044052 0.962548 0.000155 +era invasion NOUN 0.1370245521552249 0.878117 0.035357 +form medicine NOUN 0.14251446838249454 0.885405 0.035355 +equipment frequency NOUN 0.19357192826186642 0.884550 0.022608 +fight jobs NOUN 0.19540993315524777 0.971672 0.000576 +followers mark NOUN 0.21237790853979588 0.959159 0.000485 +feet hits NOUN 0.09548785108227759 0.880385 0.010662 +episode event NOUN 0.1494102309312742 0.959836 0.000107 +everything participants NOUN 0.18941449803578736 0.898186 0.010964 +example exception NOUN 0.2614222945607277 0.798057 0.053396 +episode half NOUN 0.10446821036960666 0.897726 0.031831 +form measures NOUN 0.2712571264836016 0.963104 0.000797 +example friend NOUN 0.17637863410910581 0.987285 0.000054 +environment kind NOUN 0.20037534052751993 0.888321 0.037711 +employees journalist NOUN 0.14974864545180974 0.948107 0.000087 +format implementation NOUN 0.19546048994231818 0.787767 0.044302 +episode inches NOUN 0.16092403398392396 0.925961 0.007580 +everything parents NOUN 0.1707205362581191 0.874512 0.028187 +employees investment NOUN 0.16370057860981407 0.937306 0.000699 +element hydrogen NOUN 0.06465190909405776 0.802803 0.043152 +entrance ones NOUN 0.14731900203699339 0.975671 0.000090 +engines fuel NOUN 0.2331331021811146 0.822594 0.020740 +food help NOUN 0.1635488863569225 0.861796 0.026871 +employment jobs NOUN 0.2950245620889608 0.949370 0.000468 +employees head NOUN 0.14764734504805607 0.880509 0.029897 +foot mouth NOUN 0.1255479055801575 0.962258 0.000213 +entrance park NOUN 0.1911352473996615 0.885020 0.029746 +elections laws NOUN 0.1358559363134559 0.873698 0.028387 +foot hour NOUN 0.10395598731673115 0.926304 0.001739 +fear object NOUN 0.16211945047276047 0.884469 0.032399 +fight night NOUN 0.19141602392895607 0.893862 0.022971 +event fan NOUN 0.0864105621434009 0.965946 0.000154 +estate houses NOUN 0.06003431829166051 0.960757 0.000415 +features function NOUN 0.18121097666535116 0.947912 0.001254 +event incident NOUN 0.2994896377069809 0.872522 0.034488 +employees metres NOUN 0.1708318074866934 0.896853 0.004086 +event horse NOUN 0.1089316590184849 0.860633 0.036717 +equipment household NOUN 0.14392304041509402 0.980084 0.000130 +episodes ones NOUN 0.21280778628716984 0.949209 0.000239 +features household NOUN 0.1555072625186499 0.968831 0.000545 +employment implementation NOUN 0.2386670246865022 0.960861 0.000360 +elements heritage NOUN 0.10279095706128176 0.878093 0.027066 +employment funding NOUN 0.34356941061216256 0.787751 0.036691 +entrance islands NOUN 0.19197157718646596 0.952267 0.001841 +engineer fleet NOUN 0.12353186063697183 0.882694 0.034049 +elements location NOUN 0.17616546256359844 0.959523 0.000426 +form literature NOUN 0.3122466487771046 0.973030 0.000135 +form home NOUN 0.1459449389442996 0.888388 0.028375 +environment impact NOUN 0.15889565036901201 0.879131 0.034048 +fight hit NOUN 0.1890067574285022 0.889234 0.033854 +elections jurisdiction NOUN 0.1821902921800182 0.966647 0.000196 +error image NOUN 0.12815588701084446 0.940086 0.001170 +focus motor NOUN 0.10782139032792436 0.939227 0.001352 +episodes heads NOUN 0.1397274068839858 0.943704 0.000564 +festival performances NOUN 0.1430279429367249 0.877367 0.024208 +form law NOUN 0.18920456423331014 0.884346 0.036915 +example films NOUN 0.1847351032667384 0.804492 0.046506 +features occasions NOUN 0.28257511268693286 0.902327 0.025048 +episodes forms NOUN 0.2204412725006014 0.950105 0.000021 +employees marketing NOUN 0.16027048362744245 0.949154 0.000504 +elections jobs NOUN 0.14109289758237556 0.876501 0.023745 +example models NOUN 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0.000209 +entrance hall NOUN 0.06136004351737073 0.589667 0.001195 +entertainment parent NOUN 0.1568285566653183 0.489000 0.000523 diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wordsi-rel-scores-psd.dat b/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wordsi-rel-scores-psd.dat new file mode 100644 index 00000000..62aca4bc --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wordsi-rel-scores-psd.dat @@ -0,0 +1,3 @@ +# segment k-means-f k-means-v spec-f spec-v cbc-f cbc-v online-f online-v +0 0.0 0.0 0.0 0.78574117865 0.146213151022 +1 0.0 0.0 0.0 0.0 diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wordsi-rel-scores-ukwac.dat b/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wordsi-rel-scores-ukwac.dat new file mode 100644 index 00000000..1c99f624 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wordsi-rel-scores-ukwac.dat @@ -0,0 +1,10 @@ +# segment k-means-f k-means-v spec-f spec-v cbc-f cbc-v online-f online-v +0 0.6168499780410607 0.026 0.34996606612596187 0.099 0.5984541389113184 0.029 0.42070649483011785 0.114 +1 0.0 0.0 0.29446568434857573 0.105 0.5973192045364485 0.03 0.4263025118286027 0.111 +2 0.6182347644260046 0.025 0.3082838861560848 0.099 0.606680987526181 0.027 0.434622969048288 0.106 +3 0.6182347644260046 0.025 0.3209818083128649 0.102 0.6066643650021947 0.027 0.4396114017059777 0.102 +4 0.6182347644260046 0.025 0.30988367485974805 0.101 0.6064144576155893 0.027 0.4519521696665746 0.107 +5 0.6182347644260046 0.025 0.2879237096781659 0.112 0.6064327834936453 0.027 0.44665651473456414 0.102 +6 0.6182347644260046 0.025 0.3161541493892068 0.106 0.6066828466629944 0.027 0.4660530039787947 0.1 +7 0.6182347644260046 0.025 0.27736352962896393 0.111 0.6065503232083772 0.027 0.47925044999629635 0.103 +8 0.6182347644260046 0.025 0.30397945631565915 0.115 0.6065759122790711 0.027 0.47005051219811417 0.103 diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wordsi-rel-scores-wiki.dat b/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wordsi-rel-scores-wiki.dat new file mode 100644 index 00000000..42c7dc06 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wordsi-rel-scores-wiki.dat @@ -0,0 +1,8 @@ +# segment k-means-f k-means-v spec-f spec-v cbc-f cbc-v online-f online-v +0 0.6169394515247332 0.026 0.30006338867666854 0.107 0.5983334034535096 0.029 0.3696820597461022 0.12 +1 0.20259039529214476 0.151 0.2753280705046053 0.108 0.6064228314061885 0.027 0.4308630813292238 0.109 +2 0.2041852438710118 0.149 0.2904887178693322 0.111 0.606538536740226 0.027 0.428446487711971 0.105 +3 0.2000931627629596 0.149 0.26301834098561244 0.115 0.6065344824541671 0.027 0.4396338345765405 0.106 +4 0.20499087613779554 0.15 0.2943617929001189 0.107 0.6065847624057844 0.027 0.0 0.0 +5 0.6182347644260046 0.025 0.2849325491137123 0.117 0.6065315246002058 0.027 0.4632301283274237 0.105 +6 0.6182347644260046 0.025 0.27408224438643425 0.113 0.6066635870633076 0.027 0.45631449535191093 0.101 diff --git a/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wordsi-rel-stkm.dat b/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wordsi-rel-stkm.dat new file mode 100644 index 00000000..6ff9b38c --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/figures/psd_dat/dv-wordsi-rel-stkm.dat @@ -0,0 +1,4570 @@ +# term1 term2 pos simScore psdScore +expansion move NOUN 0.17857811130419268 0.891326 0.036901 +elements maps NOUN 0.22438098708997709 0.981072 0.000070 +features nations NOUN 0.14885811927159798 0.976837 0.000012 +equation material NOUN 0.09161831370482924 0.798391 0.056198 +forest intelligence NOUN 0.1585170518151146 0.992484 0.000033 +experience plane NOUN 0.10176883802472894 0.795933 0.056613 +episodes match NOUN 0.1672617256053725 0.896224 0.034952 +fans lyrics NOUN 0.18722371001112323 0.989979 0.000054 +farmers leader NOUN 0.14627548194292497 0.896376 0.039366 +fight opening 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Klapaftis}, + title = {Sem{E}val-2010 {T}ask 14: {E}valuation {S}etting for {W}ord {S}ense {I}nduction \& {D}isambiguation {S}ystems}, + booktitle = {{NAACL-HLT} 2009 {W}orkshop on {S}emantic {E}valuations: {R}ecent {A}chievements and {F}uture {D}irections}, + location = {Boulder, Colorado, {USA}}, + year =2009, +} + +@conference{manandhar10semeval, + title={{SemEval-2010 task 14: Word sense induction \& disambiguation}}, + author={Suresh Manandhar and Ioannis P. Klapaftis and Dmitriy Dligach and Sameer S. 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Turney and Patrick Pantel}, + journal={Journal of Artificial Intelligence Research}, + volume={37}, + pages={141--188}, + year={2010} +} + +@inproceedings{utsumi10exploring, + title={{Exploring the Relationship between Semantic Spaces and Semantic Relations}}, + author={Akira Utsumi}, + booktitle = {{Proceedings of the 7th International Conference on Language Resources and Evaluation (LREC'2010)}}, + pages = {257--262}, + year = 2010, +} + +@article{zelnik04self, + title={{Self-tuning spectral clustering}}, + author={Lihi Zelnik-Manor and Pietro Perona}, + journal={Advances in neural information processing systems}, + volume={17}, + number={1601-1608}, + pages={16}, + year={2004}, + publisher={Citeseer} +} + +@TECHREPORT{zhao02criterionfunctions, + author = {Ying Zhao and George Karypis}, + title = {Criterion Functions for Document Clustering: Experiments and + Analysis}, + institution = {University of Minnesota}, + number={UMN CS 01-040}, + year = {2001} +} + +@article{zhang05improving, + journal = {Neural Processing Letters}, + title = {Improving the Robustness of ‘Online Agglomerative Clustering Method’ Based on Kernel-Induce Distance Measures}, + volume = 21, + issue = 1, + pages = {45 -- 51}, + year = 2005, + author = {Daoqiang Zhang and Songcan Chen and Keren Tan}, +} + +@inproceedings{zhao02clustering, + author = {Zhao, Ying and Karypis, George}, + title = {Evaluation of hierarchical clustering algorithms for document datasets}, + booktitle = {CIKM '02: Proceedings of the eleventh international conference on Information and knowledge management}, + year = {2002}, + isbn = {1-58113-492-4}, + pages = {515--524}, + location = {McLean, Virginia, USA}, + doi = {http://doi.acm.org/10.1145/584792.584877}, + publisher = {ACM}, + address = {New York, NY, USA}, +} + +@article{zhao05hierarchical, + author = {Ying Zhao and George Karypis}, + year = 2005, + title = {Hierarchical clustering algorithms for document datasets}, + journal = {Data Mining and Knowledge Discovery}, + volume = 10, + number = 2, + pages = {141–-168}, +} diff --git a/papers/2011_emnlp_unsup_impact/unsup-wsi-paper.tex b/papers/2011_emnlp_unsup_impact/unsup-wsi-paper.tex new file mode 100644 index 00000000..efee7154 --- /dev/null +++ b/papers/2011_emnlp_unsup_impact/unsup-wsi-paper.tex @@ -0,0 +1,769 @@ +\documentclass[11pt]{article} +\usepackage{acl-hlt2011} +\usepackage{url} +\usepackage{latexsym} +\usepackage{epsfig} +\usepackage{latexsym} +\usepackage[usenames]{color} +\usepackage{times} +\usepackage{verbatim} +\usepackage{multirow} +\usepackage{threeparttable} +\usepackage{booktabs} +\usepackage{subfig} +\usepackage{graphicx} +\usepackage[small,compact]{titlesec} +\usepackage{amsmath} +\usepackage{color} + +\usepackage[]{algorithm2e} + + +% For figure placement +\def\topfraction{.9} +\def\textfraction{0.07} %allow pages with minimal text and more figure space. +\def\floatpagefraction{.9} + +% For reducing space between bib entries +\let\oldthebibliography=\thebibliography + \let\endoldthebibliography=\endthebibliography + \renewenvironment{thebibliography}[1]{% + \begin{oldthebibliography}{#1}% + \setlength{\parskip}{0ex}% + \setlength{\itemsep}{0ex}% + }% + {% + \end{oldthebibliography}% + } + +\begin{document} + +\author{David Jurgens$^{1,2}$\\ + $^{1}$HRL Laboratories, LLC\\ + Malibu, California, USA\\ + {\tt jurgens@cs.ucla.edu} + \And + Keith Stevens$^{2}$ \\ + $^2$University of California, Los Angeles\\ + Los Angeles, California, USA\\ + {\tt kstevens@cs.ucla.edu}} + +\title{Measuring the Impact of Sense Similarity on Word Sense Induction} + +\date{} + +\maketitle + +\begin{abstract} +Word Sense Induction (WSI) is an unsupervised learning approach to discovering +the different senses of a word from its contextual uses. +A core challenge to +WSI approaches is distinguishing between related and possibly similar senses of +a word. Current WSI evaluation techniques have yet to analyze the specific +impact of similarity on accuracy. +Therefore, we present a new WSI evaluation that quantifies the relationship +between the relatedness of a word's senses and the ability of a WSI algorithm to +distinguish between them. Furthermore, we perform an analysis on sense +confusions in SemEval-2 WSI task according to sense similarity. +% +Both analyses for a representative selection of clustering-based WSI approaches +reveals that performance is most sensitive to the clustering algorithm and not +the lexical features used. + +\end{abstract} + +\section{Introduction} + +Many words in a language have several distinct meanings. For example, ``earth'' +may refer to the planet Earth, dirt, or solid ground, depending on the context. +The goal of Word Sense Induction (WSI) is to automatically discover the +different senses by examining how a word is used. This unsupervised discovery +process produces a sense inventory where the number of senses is corpus-driven +and where senses may reflect additional usages not present in a predefined sense +inventory, such as those for medicine or law \cite{dorow03discovering}. +Furthermore, these discovered senses can be used to automatically expand lexical +resources such as WordNet or FrameNet \cite{klapaftis10taxonomy}. + +Discovering the multiple senses is frequently confounded by the relationships +between a word's senses. While homonyms such as ``bass'' or ``bank'' have +unrelated senses, many polysemous words have interrelated senses, with +lexicographers often in disagreement for the number of fine-grained senses +\cite{palmer07making}. For example, the most frequent four senses for ``law'' +according to WordNet, shown in Table \ref{tab:law-senses}, are similar in +several aspects and could be ascribed interchangeably in some contexts. +% +The difficulty of automatically distinguishing two senses is proportional to +their similarity because of the increasing likelihood of the two senses sharing +similar contexts. + + +While the issue distinguishing between related senses is a recognized issue +for Word Sense Disambiguation \cite{chugur02polysemy,mccarthy06relating}, which +uses supervised training to learn sense distinctions, measuring the impact of +sense relatedness on the harder problem of WSI remains unaddressed. +% +The recent SemEval WSI tasks \cite{agirre07semeval,manandhar09semeval} have +provided a standard framework for evaluating WSI systems, with a controlled +training corpus designed to limit sense ambiguity in the example contexts. +However, given the potential relatedness of a word's senses, we view it +necessary to consider how WSI methods perform relative to the degree of +contextual ambiguity. +% +Our goal is therefore to quantify the similarity at which a WSI approach is +unable to distinguish between two senses, which reflects the sense granularity +at which the approach operates. + +\begin{table} + \footnotesize + \begin{tabular}{l p{70mm}} + \toprule + 1 & the collection of rules imposed by authority \\ + 2 & legal document setting forth rules governing a particular kind of activity \\ + 3 & a rule or body of rules of conduct inherent in human nature and essential to or binding upon human society \\ + 4 & a generalization that describes recurring facts or events in nature \\ + \bottomrule + \end{tabular} + \caption{Definitions for the top four senses of ``law'' according to WordNet} + \label{tab:law-senses} +\end{table} + +We propose two new evaluations. The first, described in Section +\ref{sec:related-senses}, uses a similarity-based pseudo-word discrimination +task to measure the discrimination capability for related senses along a graded +scale of similarity. As a second evaluation, in Section \ref{sec:semeval} we +perform an error analysis using the SemEval-2010 WSI task, examining sense +confusion relative to the sense similarities. For both evaluations, we examine +twenty different WSI clustering-based models through combining five feature +types and four clustering algorithms. These models were selected to be +representative of a wide class of existing algorithms as a way of influence +future algorithmic directions based on the current model's performance. + +\section{Clustering Contexts to Discover Senses} +\label{sec:clustering} + +Frequently, WSI is treated as an unsupervised clustering problem: The contexts +in which a word appears are clustered in order to discover its senses +\cite{navigli09word}. +We selected four diverse clustering algorithms for evaluation based on three +criteria: (1) the ability to automatically determine the final number of +clusters given an upper bound or a set of parameters, (2) an efficient run time, +and (3) high quality results in either WSI or other fields related to text +analysis. The first criteria is essential for WSI; the final number of senses +must be derived without supervision in order to reflect the true number of +senses present in the corpus. + +\paragraph{K-Means} +K-Means builds clusters based on the similarity between two data points. +Clusters grow by assigning data points to the cluster with the most similar +centroid. After every data point is assigned, each cluster's centroid is +recalculated to be the average of all the data points assigned to the cluster. +This process repeats until the centroids converge to a fixed point. We choose +initial seeds at random and use the H2 criterion function +\cite{zhao02criterionfunctions}. Although K-Means is efficient and widely used, +it requires the number of clusters to be specified a priori. Therefore, we +follow the WSI model of \newcite{pedersen06automaticcluster} and use the Gap +Statistic \cite{tibshirani00estimating} to automatically determine the number of +clusters. + +The Gap Statistic runs K-Means repeatedly with different values of $K$, ranging +from 1 to some sensible maximum. The Gap Statistic first induces a data model +from the feature distributions of the initial dataset and then for each $K$, +creates a set of artificial datasets by sampling from the derived model. $K$ is +increased until the ``gap'', i.e. the distance between the objective function +of the original dataset and the average objective function of the artificial +datasets, is larger then the gap for the previous $K$ value. We calculate the gap using +10 artificial data sets sampled from the model. + +\paragraph{Spectral Clustering} +% +Spectral Clustering interprets a dataset's elements as vertices in graph with +edges based on their similarity \cite{ng01spectral}. Clusters are found by +identifying the graph partition that produces the minimum conductance between +every partition. This can be thought of as trying to find small islands that +are connected by as few bridges as possible. We refer the reader to +\cite{von07tutorial} for further technical details. To our knowledge, only +\newcite{he10applying} have applied spectral clustering to WSI, which was +performed on a Chinese dataset. However, the algorithm used by He et +al.\ requires the number of clusters to be specified. + +We instead use a hybrid spectral clustering algorithm, first applied to +information retrieval \cite{cheng06divide}, that automatically selects the +number of clusters. This algorithm recursively partitions a dataset in half by +finding the cut that produces the minimum conductance, which builds a tree of +partitions. This split is done until either every data point is in its own +partition or a maximum number of partitions is found. Partitions are then +dynamically merged, starting at leaf partitions, based on a clustering criteria. +We use the relaxed correlation criteria \cite{cheng06divide}, +which tries to maximize both inter cluster similarity and intra cluster +dissimilarity. The final cluttering generated is then the best tree-respecting +partition of the original data set. + +\paragraph{Clustering By Committee} +Pantel and Lin \shortcite{pantel02discovering} found that K-Means clustering +folded all features found in a cluster into the centroid, many of which are not +useful for identifying the desired word sense. To overcome this, they proposed +a novel clustering algorithm for WSI, Clustering by Committee (CBC), which +includes only the most distinguishing features for a cluster into the centroid. + +For each context, an initial set of ``committees'' is formed by clustering the +most similar contexts to each context, with the resulting committees ranked to +prefer larger, highly similar clusters. The final set of committees (sense +clusters) are selected by recursively identifying the highest ranking committees +that are dissimilar to each other and then repeating the process for any +contexts not similar to existing committees. In essence, CBC aims to find the +clusters that are similar to the largest set of contexts, while keeping clusters +dissimilar from each other. CBC's recursion ensures that contexts dissimilar to +the large committees are still grouped into their own smaller committees, which +enables the discovery of infrequent senses with distinct contexts. We use a +hard sense assignment for each context, i.e., a context is labeled with only one +sense according to the most similar cluster. + +\paragraph{Streaming K-Means} +As WSI moves into inducing senses from Web-scale amounts of data, existing +clustering algorithms that keep all contexts in memory become impractical. +Jurgens and Stevens \shortcite{jurgens10hermit} proposed an on-line hybrid +clustering solution using on-line K-Means and Hierarchical Agglomerative +Clustering, which automatically decided the number of clusters without retaining +all the contexts. To the best of our knowledge, theirs is the only work using +an on-line approach. We extend this work by applying a more theoretically sound +online K-Means algorithm, called Streaming K-Means \cite{braverman11streaming}, +to WSI. We use Streaming K-Means to conduct a direct algorithmic comparison +with K-Means in the hopes that online approaches can be made just as effective +as off-line approaches. + +Streaming K-Means processes each data point only once, thus reducing the memory +overhead dramatically. Instead of recording each data point, it immediately +assigns each data point to a cluster and maintains $K \cdotp C$ clusters. $C$ varies +as the algorithm runs, initially being set to 0. When assigning a data point, +it is only assigned to an existing cluster when their similar is above some +threshold, otherwise the data point becomes the centroid of a new cluster. Once +$C$ reaches a threshold, based on an estimate of the number of data points, or +the overall K-Means clustering cost reaches some limit, the centroids are +treated as new data points and re-clustered, with the goal of merging some +centroids. We follow \cite{jurgens10hermit} and cluster the final centroids +with Hierarchical Agglomerative Clustering, with the average link criteria as +suggested by \cite{pedersen97distinguishing}. + +\section{Modeling Context} +\label{sec:context} + +For each clustering algorithm, we consider five context models that represent +the types of lexical features used by the majority of WSI approaches. + +\paragraph{Co-Occurrence} +Contexts formed from word co-occurrence are the most common in WSI algorithms. +For each occurrence of a word, those words within a certain range are counted as +features. Prior work has used a variety of context sizes, e.g. words in the same +sentence \cite{bordag06word}, in nearby lexical positions +\cite{gauch93experiments}, or within a paragraph-sized context window +\cite{pedersen10duluth}. + +We consider two co-occurrence context models: a 5-word and a 25-word window. We +note that in co-occurrence-based word space algorithms, smaller context sizes +have shown to better capture paradagmatic similarity, while larger sizes capture +semantic associativity \cite{peirsman08size,utsumi10exploring}. + +\paragraph{Dependency-Relations} + +Dependency parsing creates a syntax tree where words are directly linked +according to their relation. These links refine co-occurrence based contexts by +utilizing syntactic indications of how words are related. Dependency parsed +features have proven highly effective for word representations in many NLP +applications, e.g., \cite{pado07dependency,baroni10strudel}. We follow +\newcite{pantel02discovering} and \newcite{dorow03discovering} using the +sentence as contexts and all words with a dependency path of length 3 or less, +with the last word and its relation as a feature. We note that recently +\newcite{kern10kcdc} achieved good WSI performance with only a small, +manually-tuned subset of all relations as context. + + +\paragraph{Word Ordering} +Word ordering can provide a mild form of syntactic information +\cite{jones06high,sahlgren08permutations}. While other syntactic features may +provide significantly more information, word ordering is efficient to compute +and provides an alternative source of syntactic information for knowledge-lean +systems or for languages where NLP tools are not readily available. + +Because we treat word ordering as a syntactic feature, we limit the context to +words occurring in the same sentence. A feature is the combination of a +co-occurring word and its relative position, i.e. the same word in different +positions is treated as two separate features. + +\paragraph{Parts of Speech} +Part of speech tagging can provide a preliminary coarse-grained sense +disambiguation of a word's contextual features, where a word may have as many +senses as it does parts of speech. For example, consider an occurrence +of ``house'' in the context of ``address'' as a noun and verb: ``I went to his +house address,'' and ``I heard the legislator address the house.'' +% +Labeling ``address'' with its part of speech provides for more semantic +information on its meaning, which further constrains the sense of ``house.'' +% +Prior work \cite{pedersen97distinguishing} has suggested that this information +can improve performance, but to our knowledge, the impact of POS features has +not been evaluated in isolation. + +Each context is formed from the containing sentence; a feature is a combination +of each word and its part of speech, e.g., ``board-NOUN'' is distinct from +``board-VERB.'' + +\section{WSI Performance on Related Senses} +\label{sec:related-senses} + +\newsavebox{\tempbox} +\begin{figure*} + \vspace{-4mm} + \centering + \subfloat[5-Word Co-Occurrence]{\label{fig:co5}\includegraphics[width=0.33\textwidth]{figures/cooccurrence-5w-pwd-results.eps}} + \subfloat[25-Word Co-Occurrence]{\label{fig:co20}\includegraphics[width=0.33\textwidth]{figures/cooccurrence-20w-pwd-results.eps}} + \subfloat[Dependency Relations]{\label{fig:dp}\includegraphics[width=0.33\textwidth]{figures/dv-pwd-results.eps}} \\ + \subfloat[Word Order]{\label{fig:order}\includegraphics[width=0.33\textwidth]{figures/pos-order-results.eps}} + \subfloat[Parts of Speech]{\label{fig:pos}\includegraphics[width=0.33\textwidth]{figures/pos-pwd-results.eps}} + \subfloat[]{ + \label{fig:key} + % BEWARE: HERE BE LOTS O' BLACK MAGIC... + \vbox{% + \vfil + \hspace{-161mm} + \vspace{12mm} + \includegraphics[width=0.008\textwidth]{figures/key-test.eps} + \vfil} + }% + \caption{Pseudo-word discrimination performance } + \label{fig:pwd-results} +\end{figure*} + + +The proposed methodology measures the ability of a WSI approach to distinguish +between related senses. However, generating a large corpus with manually +labeled sense assignments and sense similarity judgements is prohibitively +expensive. Therefore, we employ a pseudo-word discrimination task +where a base word and a second word, its \emph{confounder}, are replaced +throughout the corpus with a pseudo-word. The objective is then to determine +which of the words was originally present given the context of an occurrence of +the pseudo-word. Due to not requiring manual annotation, this type of task +was initially proposed as a substitute for word sense disambiguation +\cite{schutze92context,gale92work} and for selectional +preferences \cite{clark02class}. + + + +\begin{table}[tb] + \footnotesize + \center + \begin{tabular}{ll l ll} + \toprule + \multicolumn{2}{c}{\textbf{festival}} && \multicolumn{2}{c}{\textbf{laws}} \\ + \cmidrule{1-2} \cmidrule{4-5} + offices & 0.13660 && interests & 0.18289 \\ + play & 0.13751 && politics & 0.20440 \\ + convention & 0.20296 && governments & 0.29125 \\ + tournament & 0.29007 && regulations & 0.40761 \\ + concerts & 0.48348 && legislation & 0.56112 \\ + \bottomrule + \end{tabular} + \caption{Example confounders for ``festival'' and ``laws'' and their similarities} + \label{tab:example-confounders} +\end{table} + +Following the suggestions of \newcite{chambers10improving} on designing +pseudo-words, pseudo-words were created from words with the same part of +speech and equal frequency in the training corpus. We selected nouns occurring +more than 5,000 times in a 2009 Wikipedia snapshot and then drew 5,000 contexts +for each. The snapshot was tagged with the Stanford Part of Speech Tagger +\cite{toutanova03feature} and parsed with the Malt Parser +\cite{nivre06maltparser}. + +To evaluate the impact of sense similarity, pseudo-words were created from word +pairs with a broad range of lexical similarities. We selected lexical +similarity as an approximation of sense similarity in order to model the +hypothesis that similar senses may appear in similar contexts. +Similarity scores were calculated using cosine similarity on contextual +distributions built from a sliding $\pm2$ word window over the Wikipedia corpus. +Table \ref{tab:example-confounders} highlights several example confounders and +their similarities with the base term. In total, we generated 5000 +term-confounder pairs from 98 base terms, with a mean of 51 confounders per +term. + +All clustering parameters were chosen using the default values provided in the +original papers. K-means and Streaming K-Means were both set with a maximum of +15 clusters, with the final number of clusters being determined by the data +itself. + + +\subsection{Evaluation} + +The pseudo-word's senses are induced from a training segment using each feature +and clustering combination. +% +Given that both words making up the pseudo-word may be polysemous, more than two +senses may be induced. +% +Each sense cluster is labeled according to which of the original words was +present in the majority of its contexts. For testing, each instance of the +pseudo-word in a previously unseen context is assigned the label of the cluster +to which it is most similar. We perform five-fold cross-validation, using 4,000 +contexts for training and 1,000 contexts for testing. Discrimination accuracy +is reported as the average of all five runs. Since an equal number of contexts +are used for each term, the base line accuracy of a most frequent sense model is +50\% for each pseudo-word. + +\subsection{Results and Discussion} + +Figure \ref{fig:pwd-results} shows the discrimination accuracy relative to the +similarity of a base pair and confounder, for each feature and clustering +algorithm combination. Similarity values were binned at the 0.01 level with a +mean of 39.0 scores per bin +(median=11). Because most word pairs are not related, the + distribution of similarity values is biased towards lower values. +Therefore, we omit similarity ranges above 0.5, as too few confounders occurred +in that range to draw reliable conclusions. The standard error (not shown) is +$< 1$ for all measurements. + +The general trends suggests that the clustering algorithm impacts the sense +discriminatory ability far more than the lexical feature choice. Furthermore, +sense similarity affects most clustering algorithms, with most systems seeing a +noticeable performance drop when pseudo-word similarity is increased just beyond +0. Performance at high similarity becomes more variable for all algorithms and +features. + +For each clustering algorithm, we see dramatically different trends. +% +Streaming K-Means performs well with co-occurrence based features and it does +poorly when either contexts have too many features, as in the 25 Window +Co-Occurrence feature space, or the feature space overall is too sparse, as in +the Parts of Speech and Ordering feature spaces. + +K-Means with the gap statistic converges to the most frequent sense baseline for +nearly every confounder pair. We note that this behavior significantly differs +from that seen in \cite{pedersen06automaticcluster}, which clustered +second-order co-occurrence vectors rather than the first-order features that we +use. Our analysis showed that the H2 criterion was responsible for this +behavior. A subsequent analysis revealed that K-Means still converged to MFS +for the E1, E2, I1, and I2 criterion functions \cite{zhao02criterionfunctions} +as well as when the number of artificial datasets was increased up to 100. +However, additional tests using the same features on the SemEval-1 WSI task did +not converge to MFS. Further investigation is needed to identify the cause of +convergence and what types of data are appropriate the Gap Statistic. + +Clustering by Committee performs well on most models, but significantly worse on +dependency relation features. A subsequent analysis showed that CBC +generates significantly more clusters than all other models. For the POS, 5 +word window, and 25 window Co-Occurrence feature spaces, CBC generated between +205 and 247 clusters on average, per word. With the order feature space, CBC +generated 1087 clusters per word. However, when paired with dependency relation +features, the number of clusters drops to only 78 per word. + +Spectral Clustering is most affected by sense similarity, performing +competitively for unrelated senses but dropping significantly when words become +even slightly similar. This performance drop is seen across all features. +Performance is therefore low, with the exception of dependency relations. + +Overall, these results suggest that sense relatedness is a important factor in +WSI performance and its impact should be considered in future WSI evaluations. +A potential next step is to vary the proportion of contexts from the confounder. +The current method intentionally uses a uniform distribution to avoid potential +bias; however, word sense distributions are rarely equal, and a varied +distribution would more closely model real world distributions. Similarly, the +current method tested only two senses, whereas an n-way disambiguation between +multiple confounders should also provide further insight into a WSI approach's +discriminatory abilities. + +\section{Sense Confusion in SemEval-2 Task 14} +\label{sec:semeval} + +As a second experiment, we analyze incorrect sense assignments on SemEval-2 Task +14 \cite{manandhar10semeval} to measure whether sense-relatedness biases which +sense was incorrectly selected. For WSI systems, a similarity bias would +indicate that similar senses are more likely to be incorrectly identified as a +single sense. + +We summarize Task 14 as follows. Systems are provided with an unlabeled +training corpus consisting of 879,807 multi-sentence contexts for 100 polysemous +words, comprised of 50 nouns and 50 verbs. Systems induce sense representations +for target words from the training corpus and then use those representations to +label the senses of the target words in unseen contexts from a test corpus. + +The induced senses are then evaluated against the gold standard labels OntoNotes +\cite{hovy06ontonotes} senses labels for the test corpus. For our evaluation, +we use both the two contrasting unsupervised measures, the paired FScore +\cite{artilse09role} and the V-Measure \cite{rosenberg07vmeasure}, and a +supervised measure. For each metric, we use the evaluation framework provided by the organizers of +SemEval-2 Task 14.\footnote{\tiny\url{http://www.cs.york.ac.uk/semeval2010_WSI/}} + +The V-Measure rates the homogeneity and completeness of a +clustering solution. Solutions that have word clusters formed from one +gold-standard sense are homogeneous; completeness measures the degree to which a +gold-standard sense's instances are assigned to a single cluster. +% +The paired FScore measures two types of overlap of a solution and the gold +standard in cluster assignments for all in pair-wise combination of instances. +This score tends to penalize solutions with many small clusters and highly +heterogeneous clusters \cite{manandhar09semeval}. + +The supervised evaluation measures the recall when building a Word Sense +Disambiguation classifier from the induced senses. The WSI system labels the +entire corpus, which is then divided into training and test portions. The sense +labels in the training portion are used to construct a mapping from induced +senses to the gold standard OntoNotes labels. This mapping is then evaluated +for the induced labels in the test. We report the scores for the 80\% training +and 20\% testing scenario. + +\begin{figure*}[t!f] + \vspace{-5mm} + \center + + \subfloat[Streaming K-means]{\label{fig:stkm+co}\includegraphics[width=.45\textwidth]{code/plots/semEval-2010-dv-wc-wordsi-stkm-test.key.eps}} + \subfloat[CBC]{\label{fig:stkm+wo}\includegraphics[width=.45\textwidth]{code/plots/semEval-2010-dv-wc-wordsi-cbc-test.key.eps}} \\ + \subfloat[Spectral Clustering]{\label{fig:sc+co}\includegraphics[width=.45\textwidth]{code/plots/semEval-2010-dv-wc-wordsi-sc06-test.key.eps}} + \subfloat[K-means]{\label{fig:km+co}\includegraphics[width=.45\textwidth]{code/plots/semEval-2010-dv-wc-wordsi-gs-kmeans-test.key.eps}} \\ + + \caption{The error frequency distributions for confusing the correct sense + with another sense of the given similarity when using a 5-word co-occurrence + window as context. Dashed lines indicate the null models. } + \label{fig:sense-confusion} +\end{figure*} + + +\begin{table*}[!ftb] + \center + \footnotesize + \begin{tabular}{ c c c c c c c l } + \toprule + \textbf{Context Feature} & \textbf{Clustering} & + \textbf{V-Measure} & \textbf{F-Score} & + \textbf{Recall} & \textbf{\# Clusters} & + \textbf{Purity} & \textbf{GoF p-Value} \\ + \midrule + \multirow{4}{*}{5-Word Co-Occurrence} +& Streaming & 6.7 & 55.5 & 54.8 & 4.74 & 0.103& p $<$ 2.07e-37 \\ +& Spectral & 10.8 & 39.2 & 54.3 & 8.41 & 0.194& p $<$ 1.11e-25 \\ +& CBC & 23.9 & 8.2 & 39.5 & 39.7 & 0.665& p $<$ 0.916\\ +& K-Means & 2.5 & \textbf{61.8} & \textbf{55.6} & 1.68 & 0.020 & p $<$ 1.20e-37 \\ + + \midrule + + \multirow{4}{*}{25-Word Co-Occurrence} +& Streaming & 2.6 & 61.7 & 55.5 & 1.7 & 0.020 & p $<$ 1.20e-37 \\ +& Spectral & 5.0 & 48.6 & 55.9 & 3.3 & 0.083 & p $<$ 4.36e-32 \\ +& CBC & 21.3 & 11.6 & 45.0 & 32.2 & 0.561 & p $<$ 0.011 \\ +& K-Means & 2.5 & \textbf{61.8} & \textbf{55.6} & 1.68 & 0.020 & p $<$ 1.20e-37 \\ + \midrule + + \multirow{4}{*}{Dependency Relations} +& Streaming & 3.0 & 61.5 & \textbf{55.6} & 1.9 & 0.022 & p $<$ 7.33e-38 \\ +& Spectral & 8.5 & 46.8 & 55.3 & 5.9 & 0.134 & p $<$ 5.45e-14 \\ +& CBC & 12.9 & 31.3 & 52.4 & 11.4 & 0.259 & p $<$ 4.07e-12 \\ +& K-Means & 2.5 & \textbf{61.8} & \textbf{55.6} & 1.6 & 0.020 & p $<$ 1.20e-37 \\ + \midrule + + \multirow{4}{*}{Word Order} +& Streaming & 10.8 & 43.1 & 54.2 & 10.8 & 0.300 & p $<$ 4.46e-24 \\ +& Spectral & 12.2 & 32.4 & 53.7 & 10.0 & 0.26 & p $<$ 3.27e-20 \\ +& CBC & \textbf{27.2} & 11.8 & 30.3 & 54.9 & \textbf{0.857} & p $<$ 0.999\\ +& K-Means & 2.5 & \textbf{61.8} & \textbf{55.6} & 1.6 & 0.020 & p $<$ 1.20e-37 \\ + \midrule + + \multirow{4}{*}{Parts of Speech} +& Streaming & 6.6 & 53.0 & 54.5 & 4.7 & 0.117 & p $<$ 1.06e-39 \\ +& Spectral & 10.9 & 39.4 & 53.7 & 8.3 & 0.201 & p $<$ 2.38e-13 \\ +& CBC & 23.8 & 08.0 & 40.1 & 39.7 & 0.678 & p $<$ 1.04e-2 \\ +& K-Means & 2.5 & \textbf{61.8} & \textbf{55.6} & 1.6 & 0.020 & p $<$ 1.20e-37 \\ + \midrule + \midrule + + \multicolumn{2}{r}{SemEval-2 Most Frequent Sense} +& 0.0 & 63.4 & 58.6 & 1.0 & 0.0 & p $<$ 4.244e-23 \\ + \cmidrule{3-8} + + \multicolumn{2}{r}{Best SemEval-2 FScore} +& 0.0 & 63.3 & 58.6 & 1.0 & 0.0 & p $<$ 2.893e-23 \\ + \cmidrule{3-8} + \multicolumn{2}{r}{Best SemEval-2 VMeasure} +& 16.2 & 26.7 & 58.3 & 10.7 & 0.367 & p $<$ 1.956e-14 \\ + \cmidrule{3-8} + \multicolumn{2}{r}{Best SemEval-2 Supervised Recall} +& 15.7 & 49.7 & 62.4 & 11.5 & 0.187 & p $<$ 8.910e-19 \\ + \bottomrule + + \end{tabular} + \caption{Unsupervised and Supervised scores on the SemEval-2010 WSI Task for + each feature and clustering models, with reference scores for the top + performing systems for each evaluation shown below.} + \label{tab:semeval-scores} +\end{table*} + +\subsection{Evaluation} + + +We expect that if sense similarity is a factor in sense confusion, the +probability of confusion will increase with sense similarity. Therefore, we +measure the probability of labeling an instance with the incorrect OntoNotes +sense relative to the sense similarity with the gold standard sense. + +In order to calculate the incorrect assignments, the induced senses must be +mapped to OntoNotes senses. +% +Each induced sense, $s_i$, is mapped to the OntoNotes sense that occurs most +frequently among the instances in the test corpus that are assigned induced +sense $s_i$. +We note that this labeling process is only an approximate solution to assigning +gold standard labels to induced senses. A more robust labeling could take into +account the distribution of gold standard senses labels in the corpus from which +the senses are induced; however, such labels are not available in the Task 14 +training corpus. + + +For each incorrect sense assignment, we measure the similarity of the confused +sense to the correct sense. To our knowledge, no work has been done on +calculating sense similarity within the OntoNotes sense hierarchy.\footnote{We + suspect that this is in part because a word's OntoNotes senses have been + designed to minimize sense confusion.} Therefore, we approximate OntoNotes +sense similarity by using sense similarity in the WordNet ontology, on which has +many similarity measures have been defined. Following +\newcite{budanitsky06evaluating}, we estimate the WordNet sense similarity using +the method proposed by \newcite{jiang97semantic}. + + +Each OntoNotes sense $s^i$ is mapped to a set of WordNet 3.0 senses $S^i = +\{wn_1, \ldots, wn_n\}$ using the sense mapping provided by the CoNLL shared +task.\footnote{\tiny\url{http://conll.bbn.com/index.php/data.html}} The sense +% +similarity for two OntoNotes senses is computed using one of two methods: +\begin{equation} +\label{eq:avg} +sim=\frac{1}{|S^1||S^2|}\sum_{wn^i \in S^1, wn^j \in S^2} JCN(wn^i, wn^j), +\end{equation} +\vspace{-1mm} +or +\vspace{-2mm} +\begin{equation} +\label{eq:max} +sim = \underset{wn^i \in S^1, wn^j \in S^2}{\operatorname{argmax}} JCN(wn^i, wn^j), +\end{equation} +where $JCN$ indicates the Jiang-Conrath similarity of two WordNet senses, +calculated using WordNet::Similarity \cite{pedersen04wordnet}. +Eq.\ \ref{eq:avg} computes similarity as the average similarity of all pair-wise +WordNet sense combinations, while Eq.\ \ref{eq:max} uses the highest similarity. +The resulting OntoNote sense similarities range from 0 to 1, with 1 being +maximally similar. +% +We excluded 10 words from the test set that did not have mappings from OntoNotes +to WordNet 3.0 senses, and additional 23 words that only had two senses, +which prevented testing for a similarity bias. The remaining 67 words +yielded 4,097 test instances for evaluation. + +Each instance of the test corpus was tested for +sense confusion, recording the similarity of the incorrectly assigned sense and +the gold standard sense. The resulting incorrect assignments are transformed +into an error distribution according by accumulating error counts into +similarity bins where each bin has a range of 0.02. We analyze the WSI systems +defined in section \ref{sec:related-senses} as well as the results of three +systems that participated in Task 14 and scored the highest on the paired +FScore, V-measure, or Supervised Recall evaluations. + +To quantify the impact, we compare each system's error distribution against a +null model over the set of incorrect test instances missed by that system. In +the null model, the incorrect sense for each instance is selected with uniform +probability from the available senses. This behavior produces a distribution +with no similarity bias. The cumulative error distribution for the null model +is not uniform due to multiple sense pairings having the same +similarity.\footnote{Verb senses often have a JCN similarity of 0 due to having + no shared parent within the WordNet verb sense hierarchy, which results in + high frequency distribution around 0.} To quantify the difference between a +system's error distribution and corresponding null model, we calculate the +G-test as a measure of Goodness of Fit (GoF). The resulting p-values reflect +the probability of observing the system's error distribution if there was no +bias from sense-similarity. + + +\subsection{Results and Discussion} + +We compare the error analysis against the evaluation measures of Task 14. Table +\ref{tab:semeval-scores} displays the evaluation measures. We also report the +average number of clusters per word, the cluster purity, and the p-value when +using Eq.\ \ref{eq:max} to measure sense similarity. +% +Figure \ref{fig:sense-confusion} visualizes the error distributions for the four +clustering algorithms on 5-word co-occurrence features. The distributions in +Figure \ref{fig:sense-confusion} are representative of those of the other +context models, which we omit due to space. Each plot reflects the frequency at +which a sense with the specified similarity was confused for the correct sense. + +The low p-values in Table \ref{tab:semeval-scores} indicate a significant +deviation from the null model. Examining the shape of the error distribution in +Figure \ref{fig:sense-confusion} reveals a noticeable skew towards higher +similarity when an incorrect sense assignment is made. This distribution skew +is also consistent for both similarity measures. + +Comparing the Task 14 results in Table \ref{tab:semeval-scores} to the sense +confusion trends in in Figure \ref{fig:sense-confusion} highlights an +interesting pattern among the various models: as the number of induced sense +clusters increases, the error distribution better approximates the null model. +% +Specifically, the GoF for all models was well correlated with cluster purity +($\rho$=0.66), and the number of clusters ($\rho$=0.76). +CBC generated the highest number of clusters and has a sense confusion +distribution that closely matches the null model, indicating that it is less +affected by sense similarity. +In comparison, all of the Streaming K-Means models, which have the fewest +clusters, differ noticeably from the null model. Spectral Clustering, which +also generates fewer clusters than CBC, has an observed confusion rate that +differs from the baseline. K-Means again reduces to the MFS baseline. + +When comparing along the feature sets, we see that on average Word Order +features generate the highest V-Measure scores, highest purity, and highest +p-values for Streaming K-Means and CBC. This result correlates well with the +average number of features seen per context: Word Order contexts used 0.03\% of +the feature space while contexts in other feature spaces used between 0.07\% and +0.12\% of the feature space, suggesting that the SemEval measures are determined +in part by feature space density. Similarly, 25-word co-occurrence features had +the highest percentage of features used per context, 0.12\%, and generated the +lowest V-Measure, purity score, and p-value for 3 clustering models. + + +These scores support another known trend in the SemEval-2 evaluation: the +performance on the V-Measure is proportional to the number of induced sense +clusters, while the paired FScore is inversely proportional. But what is +surprising is that models which perform well against the V-Measure also exhibit +a smaller sense similarity bias, suggesting that CBC and similar clustering +methods are suitable for situations where competing senses of a word have a high +degree of overlap. + + +As a final comparison, we also computed the sense bias for the top 3 SemEval +systems under each measure. The best of these models are listed in Table +\ref{tab:semeval-scores}. We did not find any consistent trends between the +V-Measure, purity, and p-value among these models. The top F-Scoring models all +used either a first or second order co-occurrence feature space similar to ours +\cite{kern10kcdc,pedersen10duluth}, whereas the top supervised score was +achieved by a graph-based system \cite{klapaftis08word}. + +\section{Future Work and Conclusion} + +We presented a two evaluation for WSI approaches and examined the performance of +a wide range of algorithms. The results raise a potential issue for +clustering-based WSI approaches: sense discrimination degrades notably as the +sense relatedness increases. We highlight three potential avenues for future +research. First, this methodology should be applied to additional WSI models, +such as graph-based \cite{klapaftis08word,navigli10inducing} and probabilistic +models \cite{dinu10measuring,elshamy10ksu}. +% +Second, we plan to extend the analysis to different sense distributions, varying +number of senses, and for human annotated sense similarity data. +% +Third, this evaluation makes the simplifying assumption of one sense per +instance; however, \newcite{erk09investigations} note that the relations between +senses may cause a single word instance to evoke multiple senses within the same +context. Therefore, a future experiment should consider how WSI systems might +address learning senses given the presence of multiple, similar senses for a +single instance. + +All models, associated data sets, testing framework, and scores have been +released as a part of the open-source S-Space Package +\cite{jurgens10sspace}.\footnote{ \tiny\url{http://code.google.com/p/airhead-research/}} + +\bibliographystyle{acl} +\bibliography{unsup-wsi-paper} + +\end{document} diff --git a/papers/2012_emnlp_topic_coherence/acl.bst b/papers/2012_emnlp_topic_coherence/acl.bst new file mode 100644 index 00000000..ab0811e4 --- /dev/null +++ b/papers/2012_emnlp_topic_coherence/acl.bst @@ -0,0 +1,1321 @@ +% BibTeX `acl' style file for BibTeX version 0.99c, LaTeX version 2.09 +% This version was made by modifying `aaai-named' format based on the master +% file by Oren Patashnik (PATASHNIK@SCORE.STANFORD.EDU) + +% Copyright (C) 1985, all rights reserved. +% Modifications Copyright 1988, Peter F. Patel-Schneider +% Further modifictions by Stuart Shieber, 1991, and Fernando Pereira, 1992. +% Copying of this file is authorized only if either +% (1) you make absolutely no changes to your copy, including name, or +% (2) if you do make changes, you name it something other than +% btxbst.doc, plain.bst, unsrt.bst, alpha.bst, and abbrv.bst. +% This restriction helps ensure that all standard styles are identical. + +% There are undoubtably bugs in this style. If you make bug fixes, +% improvements, etc. please let me know. My e-mail address is: +% pfps@spar.slb.com + +% Citation format: [author-last-name, year] +% [author-last-name and author-last-name, year] +% [author-last-name {\em et al.}, year] +% +% Reference list ordering: alphabetical by author or whatever passes +% for author in the absence of one. +% +% This BibTeX style has support for short (year only) citations. This +% is done by having the citations actually look like +% \citename{name-info, }year +% The LaTeX style has to have the following +% \let\@internalcite\cite +% \def\cite{\def\citename##1{##1}\@internalcite} +% \def\shortcite{\def\citename##1{}\@internalcite} +% \def\@biblabel#1{\def\citename##1{##1}[#1]\hfill} +% which makes \shortcite the macro for short citations. + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% Changes made by SMS for thesis style +% no emphasis on "et al." +% "Ph.D." includes periods (not "PhD") +% moved year to immediately after author's name +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +ENTRY + { address + author + booktitle + chapter + edition + editor + howpublished + institution + journal + key + month + note + number + organization + pages + publisher + school + series + title + type + volume + year + } + {} + { label extra.label sort.label } + +INTEGERS { output.state before.all mid.sentence after.sentence after.block } + +FUNCTION {init.state.consts} +{ #0 'before.all := + #1 'mid.sentence := + #2 'after.sentence := + #3 'after.block := +} + +STRINGS { s t } + +FUNCTION {output.nonnull} +{ 's := + output.state mid.sentence = + { ", " * write$ } + { output.state after.block = + { add.period$ write$ + newline$ + "\newblock " write$ + } + { output.state before.all = + 'write$ + { add.period$ " " * write$ } + if$ + } + if$ + mid.sentence 'output.state := + } + if$ + s +} + +FUNCTION {output} +{ duplicate$ empty$ + 'pop$ + 'output.nonnull + if$ +} + +FUNCTION {output.check} +{ 't := + duplicate$ empty$ + { pop$ "empty " t * " in " * cite$ * warning$ } + 'output.nonnull + if$ +} + +FUNCTION {output.bibitem} +{ newline$ + + "\bibitem[" write$ + label write$ + "]{" write$ + + cite$ write$ + "}" write$ + newline$ + "" + before.all 'output.state := +} + +FUNCTION {fin.entry} +{ add.period$ + write$ + newline$ +} + +FUNCTION {new.block} +{ output.state before.all = + 'skip$ + { after.block 'output.state := } + if$ +} + +FUNCTION {new.sentence} +{ output.state after.block = + 'skip$ + { output.state before.all = + 'skip$ + { after.sentence 'output.state := } + if$ + } + if$ +} + +FUNCTION {not} +{ { #0 } + { #1 } + if$ +} + +FUNCTION {and} +{ 'skip$ + { pop$ #0 } + if$ +} + +FUNCTION {or} +{ { pop$ #1 } + 'skip$ + if$ +} + +FUNCTION {new.block.checka} +{ empty$ + 'skip$ + 'new.block + if$ +} + +FUNCTION {new.block.checkb} +{ empty$ + swap$ empty$ + and + 'skip$ + 'new.block + if$ +} + +FUNCTION {new.sentence.checka} +{ empty$ + 'skip$ + 'new.sentence + if$ +} + +FUNCTION {new.sentence.checkb} +{ empty$ + swap$ empty$ + and + 'skip$ + 'new.sentence + if$ +} + +FUNCTION {field.or.null} +{ duplicate$ empty$ + { pop$ "" } + 'skip$ + if$ +} + +FUNCTION {emphasize} +{ duplicate$ empty$ + { pop$ "" } + { "{\em " swap$ * "}" * } + if$ +} + +INTEGERS { nameptr namesleft numnames } + +FUNCTION {format.names} +{ 's := + #1 'nameptr := + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + + { s nameptr "{ff~}{vv~}{ll}{, jj}" format.name$ 't := + + nameptr #1 > + { namesleft #1 > + { ", " * t * } + { numnames #2 > + { "," * } + 'skip$ + if$ + t "others" = + { " et~al." * } + { " and " * t * } + if$ + } + if$ + } + 't + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {format.authors} +{ author empty$ + { "" } + { author format.names } + if$ +} + +FUNCTION {format.editors} +{ editor empty$ + { "" } + { editor format.names + editor num.names$ #1 > + { ", editors" * } + { ", editor" * } + if$ + } + if$ +} + +FUNCTION {format.title} +{ title empty$ + { "" } + + { title "t" change.case$ } + + if$ +} + +FUNCTION {n.dashify} +{ 't := + "" + { t empty$ not } + { t #1 #1 substring$ "-" = + { t #1 #2 substring$ "--" = not + { "--" * + t #2 global.max$ substring$ 't := + } + { { t #1 #1 substring$ "-" = } + { "-" * + t #2 global.max$ substring$ 't := + } + while$ + } + if$ + } + { t #1 #1 substring$ * + t #2 global.max$ substring$ 't := + } + if$ + } + while$ +} + +FUNCTION {format.date} +{ year empty$ + { month empty$ + { "" } + { "there's a month but no year in " cite$ * warning$ + month + } + if$ + } + { month empty$ + { "" } + { month } + if$ + } + if$ +} + +FUNCTION {format.btitle} +{ title emphasize +} + +FUNCTION {tie.or.space.connect} +{ duplicate$ text.length$ #3 < + { "~" } + { " " } + if$ + swap$ * * +} + +FUNCTION {either.or.check} +{ empty$ + 'pop$ + { "can't use both " swap$ * " fields in " * cite$ * warning$ } + if$ +} + +FUNCTION {format.bvolume} +{ volume empty$ + { "" } + { "volume" volume tie.or.space.connect + series empty$ + 'skip$ + { " of " * series emphasize * } + if$ + "volume and number" number either.or.check + } + if$ +} + +FUNCTION {format.number.series} +{ volume empty$ + { number empty$ + { series field.or.null } + { output.state mid.sentence = + { "number" } + { "Number" } + if$ + number tie.or.space.connect + series empty$ + { "there's a number but no series in " cite$ * warning$ } + { " in " * series * } + if$ + } + if$ + } + { "" } + if$ +} + +FUNCTION {format.edition} +{ edition empty$ + { "" } + { output.state mid.sentence = + { edition "l" change.case$ " edition" * } + { edition "t" change.case$ " edition" * } + if$ + } + if$ +} + +INTEGERS { multiresult } + +FUNCTION {multi.page.check} +{ 't := + #0 'multiresult := + { multiresult not + t empty$ not + and + } + { t #1 #1 substring$ + duplicate$ "-" = + swap$ duplicate$ "," = + swap$ "+" = + or or + { #1 'multiresult := } + { t #2 global.max$ substring$ 't := } + if$ + } + while$ + multiresult +} + +FUNCTION {format.pages} +{ pages empty$ + { "" } + { pages multi.page.check + { "pages" pages n.dashify tie.or.space.connect } + { "page" pages tie.or.space.connect } + if$ + } + if$ +} + +FUNCTION {format.year.label} +{ year extra.label * +} + +FUNCTION {format.vol.num.pages} +{ volume field.or.null + number empty$ + 'skip$ + { "(" number * ")" * * + volume empty$ + { "there's a number but no volume in " cite$ * warning$ } + 'skip$ + if$ + } + if$ + pages empty$ + 'skip$ + { duplicate$ empty$ + { pop$ format.pages } + { ":" * pages n.dashify * } + if$ + } + if$ +} + +FUNCTION {format.chapter.pages} +{ chapter empty$ + 'format.pages + { type empty$ + { "chapter" } + { type "l" change.case$ } + if$ + chapter tie.or.space.connect + pages empty$ + 'skip$ + { ", " * format.pages * } + if$ + } + if$ +} + +FUNCTION {format.in.ed.booktitle} +{ booktitle empty$ + { "" } + { editor empty$ + { "In " booktitle emphasize * } + { "In " format.editors * ", " * booktitle emphasize * } + if$ + } + if$ +} + +FUNCTION {empty.misc.check} +{ author empty$ title empty$ howpublished empty$ + month empty$ year empty$ note empty$ + and and and and and + + key empty$ not and + + { "all relevant fields are empty in " cite$ * warning$ } + 'skip$ + if$ +} + +FUNCTION {format.thesis.type} +{ type empty$ + 'skip$ + { pop$ + type "t" change.case$ + } + if$ +} + +FUNCTION {format.tr.number} +{ type empty$ + { "Technical Report" } + 'type + if$ + number empty$ + { "t" change.case$ } + { number tie.or.space.connect } + if$ +} + +FUNCTION {format.article.crossref} +{ key empty$ + { journal empty$ + { "need key or journal for " cite$ * " to crossref " * crossref * + warning$ + "" + } + { "In {\em " journal * "\/}" * } + if$ + } + { "In " key * } + if$ + " \cite{" * crossref * "}" * +} + +FUNCTION {format.crossref.editor} +{ editor #1 "{vv~}{ll}" format.name$ + editor num.names$ duplicate$ + #2 > + { pop$ " et~al." * } + { #2 < + 'skip$ + { editor #2 "{ff }{vv }{ll}{ jj}" format.name$ "others" = + { " et~al." * } + { " and " * editor #2 "{vv~}{ll}" format.name$ * } + if$ + } + if$ + } + if$ +} + +FUNCTION {format.book.crossref} +{ volume empty$ + { "empty volume in " cite$ * "'s crossref of " * crossref * warning$ + "In " + } + { "Volume" volume tie.or.space.connect + " of " * + } + if$ + editor empty$ + editor field.or.null author field.or.null = + or + { key empty$ + { series empty$ + { "need editor, key, or series for " cite$ * " to crossref " * + crossref * warning$ + "" * + } + { "{\em " * series * "\/}" * } + if$ + } + { key * } + if$ + } + { format.crossref.editor * } + if$ + " \cite{" * crossref * "}" * +} + +FUNCTION {format.incoll.inproc.crossref} +{ editor empty$ + editor field.or.null author field.or.null = + or + { key empty$ + { booktitle empty$ + { "need editor, key, or booktitle for " cite$ * " to crossref " * + crossref * warning$ + "" + } + { "In {\em " booktitle * "\/}" * } + if$ + } + { "In " key * } + if$ + } + { "In " format.crossref.editor * } + if$ + " \cite{" * crossref * "}" * +} + +FUNCTION {article} +{ output.bibitem + format.authors "author" output.check + new.block + format.year.label "year" output.check + new.block + format.title "title" output.check + new.block + crossref missing$ + { journal emphasize "journal" output.check + format.vol.num.pages output + format.date output + } + { format.article.crossref output.nonnull + format.pages output + } + if$ + new.block + note output + fin.entry +} + +FUNCTION {book} +{ output.bibitem + author empty$ + { format.editors "author and editor" output.check } + { format.authors output.nonnull + crossref missing$ + { "author and editor" editor either.or.check } + 'skip$ + if$ + } + if$ + new.block + format.year.label "year" output.check + new.block + format.btitle "title" output.check + crossref missing$ + { format.bvolume output + new.block + format.number.series output + new.sentence + publisher "publisher" output.check + address output + } + { new.block + format.book.crossref output.nonnull + } + if$ + format.edition output + format.date output + new.block + note output + fin.entry +} + +FUNCTION {booklet} +{ output.bibitem + format.authors output + new.block + format.year.label "year" output.check + new.block + format.title "title" output.check + howpublished address new.block.checkb + howpublished output + address output + format.date output + new.block + note output + fin.entry +} + +FUNCTION {inbook} +{ output.bibitem + author empty$ + { format.editors "author and editor" output.check } + { format.authors output.nonnull + crossref missing$ + { "author and editor" editor either.or.check } + 'skip$ + if$ + } + if$ + format.year.label "year" output.check + new.block + new.block + format.btitle "title" output.check + crossref missing$ + { format.bvolume output + format.chapter.pages "chapter and pages" output.check + new.block + format.number.series output + new.sentence + publisher "publisher" output.check + address output + } + { format.chapter.pages "chapter and pages" output.check + new.block + format.book.crossref output.nonnull + } + if$ + format.edition output + format.date output + new.block + note output + fin.entry +} + +FUNCTION {incollection} +{ output.bibitem + format.authors "author" output.check + new.block + format.year.label "year" output.check + new.block + format.title "title" output.check + new.block + crossref missing$ + { format.in.ed.booktitle "booktitle" output.check + format.bvolume output + format.number.series output + format.chapter.pages output + new.sentence + publisher "publisher" output.check + address output + format.edition output + format.date output + } + { format.incoll.inproc.crossref output.nonnull + format.chapter.pages output + } + if$ + new.block + note output + fin.entry +} + +FUNCTION {inproceedings} +{ output.bibitem + format.authors "author" output.check + new.block + format.year.label "year" output.check + new.block + format.title "title" output.check + new.block + crossref missing$ + { format.in.ed.booktitle "booktitle" output.check + format.bvolume output + format.number.series output + format.pages output + address empty$ + { organization publisher new.sentence.checkb + organization output + publisher output + format.date output + } + { address output.nonnull + format.date output + new.sentence + organization output + publisher output + } + if$ + } + { format.incoll.inproc.crossref output.nonnull + format.pages output + } + if$ + new.block + note output + fin.entry +} + +FUNCTION {conference} { inproceedings } + +FUNCTION {manual} +{ output.bibitem + author empty$ + { organization empty$ + 'skip$ + { organization output.nonnull + address output + } + if$ + } + { format.authors output.nonnull } + if$ + format.year.label "year" output.check + new.block + new.block + format.btitle "title" output.check + author empty$ + { organization empty$ + { address new.block.checka + address output + } + 'skip$ + if$ + } + { organization address new.block.checkb + organization output + address output + } + if$ + format.edition output + format.date output + new.block + note output + fin.entry +} + +FUNCTION {mastersthesis} +{ output.bibitem + format.authors "author" output.check + new.block + format.year.label "year" output.check + new.block + format.title "title" output.check + new.block + "Master's thesis" format.thesis.type output.nonnull + school "school" output.check + address output + format.date output + new.block + note output + fin.entry +} + +FUNCTION {misc} +{ output.bibitem + format.authors output + new.block + format.year.label output + new.block + title howpublished new.block.checkb + format.title output + howpublished new.block.checka + howpublished output + format.date output + new.block + note output + fin.entry + empty.misc.check +} + +FUNCTION {phdthesis} +{ output.bibitem + format.authors "author" output.check + new.block + format.year.label "year" output.check + new.block + format.btitle "title" output.check + new.block + "{Ph.D.} thesis" format.thesis.type output.nonnull + school "school" output.check + address output + format.date output + new.block + note output + fin.entry +} + +FUNCTION {proceedings} +{ output.bibitem + editor empty$ + { organization output } + { format.editors output.nonnull } + if$ + new.block + format.year.label "year" output.check + new.block + format.btitle "title" output.check + format.bvolume output + format.number.series output + address empty$ + { editor empty$ + { publisher new.sentence.checka } + { organization publisher new.sentence.checkb + organization output + } + if$ + publisher output + format.date output + } + { address output.nonnull + format.date output + new.sentence + editor empty$ + 'skip$ + { organization output } + if$ + publisher output + } + if$ + new.block + note output + fin.entry +} + +FUNCTION {techreport} +{ output.bibitem + format.authors "author" output.check + new.block + format.year.label "year" output.check + new.block + format.title "title" output.check + new.block + format.tr.number output.nonnull + institution "institution" output.check + address output + format.date output + new.block + note output + fin.entry +} + +FUNCTION {unpublished} +{ output.bibitem + format.authors "author" output.check + new.block + format.year.label "year" output.check + new.block + format.title "title" output.check + new.block + note "note" output.check + format.date output + fin.entry +} + +FUNCTION {default.type} { misc } + +MACRO {jan} {"January"} + +MACRO {feb} {"February"} + +MACRO {mar} {"March"} + +MACRO {apr} {"April"} + +MACRO {may} {"May"} + +MACRO {jun} {"June"} + +MACRO {jul} {"July"} + +MACRO {aug} {"August"} + +MACRO {sep} {"September"} + +MACRO {oct} {"October"} + +MACRO {nov} {"November"} + +MACRO {dec} {"December"} + +MACRO {acmcs} {"ACM Computing Surveys"} + +MACRO {acta} {"Acta Informatica"} + +MACRO {cacm} {"Communications of the ACM"} + +MACRO {ibmjrd} {"IBM Journal of Research and Development"} + +MACRO {ibmsj} {"IBM Systems Journal"} + +MACRO {ieeese} {"IEEE Transactions on Software Engineering"} + +MACRO {ieeetc} {"IEEE Transactions on Computers"} + +MACRO {ieeetcad} + {"IEEE Transactions on Computer-Aided Design of Integrated Circuits"} + +MACRO {ipl} {"Information Processing Letters"} + +MACRO {jacm} {"Journal of the ACM"} + +MACRO {jcss} {"Journal of Computer and System Sciences"} + +MACRO {scp} {"Science of Computer Programming"} + +MACRO {sicomp} {"SIAM Journal on Computing"} + +MACRO {tocs} {"ACM Transactions on Computer Systems"} + +MACRO {tods} {"ACM Transactions on Database Systems"} + +MACRO {tog} {"ACM Transactions on Graphics"} + +MACRO {toms} {"ACM Transactions on Mathematical Software"} + +MACRO {toois} {"ACM Transactions on Office Information Systems"} + +MACRO {toplas} {"ACM Transactions on Programming Languages and Systems"} + +MACRO {tcs} {"Theoretical Computer Science"} + +READ + +FUNCTION {sortify} +{ purify$ + "l" change.case$ +} + +INTEGERS { len } + +FUNCTION {chop.word} +{ 's := + 'len := + s #1 len substring$ = + { s len #1 + global.max$ substring$ } + 's + if$ +} + +INTEGERS { et.al.char.used } + +FUNCTION {initialize.et.al.char.used} +{ #0 'et.al.char.used := +} + +EXECUTE {initialize.et.al.char.used} + +FUNCTION {format.lab.names} +{ 's := + s num.names$ 'numnames := + + numnames #1 = + { s #1 "{vv }{ll}" format.name$ } + { numnames #2 = + { s #1 "{vv }{ll }and " format.name$ s #2 "{vv }{ll}" format.name$ * + } + { s #1 "{vv }{ll }\bgroup et al.\egroup " format.name$ } + if$ + } + if$ + +} + +FUNCTION {author.key.label} +{ author empty$ + { key empty$ + + { cite$ #1 #3 substring$ } + + { key #3 text.prefix$ } + if$ + } + { author format.lab.names } + if$ +} + +FUNCTION {author.editor.key.label} +{ author empty$ + { editor empty$ + { key empty$ + + { cite$ #1 #3 substring$ } + + { key #3 text.prefix$ } + if$ + } + { editor format.lab.names } + if$ + } + { author format.lab.names } + if$ +} + +FUNCTION {author.key.organization.label} +{ author empty$ + { key empty$ + { organization empty$ + + { cite$ #1 #3 substring$ } + + { "The " #4 organization chop.word #3 text.prefix$ } + if$ + } + { key #3 text.prefix$ } + if$ + } + { author format.lab.names } + if$ +} + +FUNCTION {editor.key.organization.label} +{ editor empty$ + { key empty$ + { organization empty$ + + { cite$ #1 #3 substring$ } + + { "The " #4 organization chop.word #3 text.prefix$ } + if$ + } + { key #3 text.prefix$ } + if$ + } + { editor format.lab.names } + if$ +} + +FUNCTION {calc.label} +{ type$ "book" = + type$ "inbook" = + or + 'author.editor.key.label + { type$ "proceedings" = + 'editor.key.organization.label + { type$ "manual" = + 'author.key.organization.label + 'author.key.label + if$ + } + if$ + } + if$ + duplicate$ + + "\protect\citename{" swap$ * "}" * + year field.or.null purify$ * + 'label := + year field.or.null purify$ * + + sortify 'sort.label := +} + +FUNCTION {sort.format.names} +{ 's := + #1 'nameptr := + "" + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + { nameptr #1 > + { " " * } + 'skip$ + if$ + + s nameptr "{vv{ } }{ll{ }}{ ff{ }}{ jj{ }}" format.name$ 't := + + nameptr numnames = t "others" = and + { "et al" * } + { t sortify * } + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {sort.format.title} +{ 't := + "A " #2 + "An " #3 + "The " #4 t chop.word + chop.word + chop.word + sortify + #1 global.max$ substring$ +} + +FUNCTION {author.sort} +{ author empty$ + { key empty$ + { "to sort, need author or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { author sort.format.names } + if$ +} + +FUNCTION {author.editor.sort} +{ author empty$ + { editor empty$ + { key empty$ + { "to sort, need author, editor, or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { editor sort.format.names } + if$ + } + { author sort.format.names } + if$ +} + +FUNCTION {author.organization.sort} +{ author empty$ + { organization empty$ + { key empty$ + { "to sort, need author, organization, or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { "The " #4 organization chop.word sortify } + if$ + } + { author sort.format.names } + if$ +} + +FUNCTION {editor.organization.sort} +{ editor empty$ + { organization empty$ + { key empty$ + { "to sort, need editor, organization, or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { "The " #4 organization chop.word sortify } + if$ + } + { editor sort.format.names } + if$ +} + +FUNCTION {presort} + +{ calc.label + sort.label + " " + * + type$ "book" = + + type$ "inbook" = + or + 'author.editor.sort + { type$ "proceedings" = + 'editor.organization.sort + { type$ "manual" = + 'author.organization.sort + 'author.sort + if$ + } + if$ + } + if$ + + * + + " " + * + year field.or.null sortify + * + " " + * + title field.or.null + sort.format.title + * + #1 entry.max$ substring$ + 'sort.key$ := +} + +ITERATE {presort} + +SORT + +STRINGS { longest.label last.sort.label next.extra } + +INTEGERS { longest.label.width last.extra.num } + +FUNCTION {initialize.longest.label} +{ "" 'longest.label := + #0 int.to.chr$ 'last.sort.label := + "" 'next.extra := + #0 'longest.label.width := + #0 'last.extra.num := +} + +FUNCTION {forward.pass} +{ last.sort.label sort.label = + { last.extra.num #1 + 'last.extra.num := + last.extra.num int.to.chr$ 'extra.label := + } + { "a" chr.to.int$ 'last.extra.num := + "" 'extra.label := + sort.label 'last.sort.label := + } + if$ +} + +FUNCTION {reverse.pass} +{ next.extra "b" = + { "a" 'extra.label := } + 'skip$ + if$ + label extra.label * 'label := + label width$ longest.label.width > + { label 'longest.label := + label width$ 'longest.label.width := + } + 'skip$ + if$ + extra.label 'next.extra := +} + +EXECUTE {initialize.longest.label} + +ITERATE {forward.pass} + +REVERSE {reverse.pass} + +FUNCTION {begin.bib} + +{ et.al.char.used + { "\newcommand{\etalchar}[1]{$^{#1}$}" write$ newline$ } + 'skip$ + if$ + preamble$ empty$ + + 'skip$ + { preamble$ write$ newline$ } + if$ + + "\begin{thebibliography}{" "}" * write$ newline$ + +} + +EXECUTE {begin.bib} + +EXECUTE {init.state.consts} + +ITERATE {call.type$} + +FUNCTION {end.bib} +{ newline$ + "\end{thebibliography}" write$ newline$ +} + +EXECUTE {end.bib} + diff --git a/papers/2012_emnlp_topic_coherence/acl2010.sty b/papers/2012_emnlp_topic_coherence/acl2010.sty new file mode 100644 index 00000000..8462da37 --- /dev/null +++ b/papers/2012_emnlp_topic_coherence/acl2010.sty @@ -0,0 +1,370 @@ +% File acl2010.sty +% same as -- +% File acl-ijcnlp2009.sty +% same as -- +% File eacl2006.sty +% September 19, 2005 +% Contact: e.agirre@ehu.es or Sergi.Balari@uab.es + +% This is the LaTeX style file for EACL 2006. It is nearly identical to the +% style files for ACL2005, ACL 2002, ACL 2001, ACL 2000, EACL 95 and EACL +% 99. +% +% Changes made include: adapt layout to A4 and centimeters, widden abstract + +% This is the LaTeX style file for ACL 2000. It is nearly identical to the +% style files for EACL 95 and EACL 99. Minor changes include editing the +% instructions to reflect use of \documentclass rather than \documentstyle +% and removing the white space before the title on the first page +% -- John Chen, June 29, 2000 + +% To convert from submissions prepared using the style file aclsub.sty +% prepared for the ACL 2000 conference, proceed as follows: +% 1) Remove submission-specific information: \whichsession, \id, +% \wordcount, \otherconferences, \area, \keywords +% 2) \summary should be removed. The summary material should come +% after \maketitle and should be in the ``abstract'' environment +% 3) Check all citations. This style should handle citations correctly +% and also allows multiple citations separated by semicolons. +% 4) Check figures and examples. Because the final format is double- +% column, some adjustments may have to be made to fit text in the column +% or to choose full-width (\figure*} figures. +% 5) Change the style reference from aclsub to acl2000, and be sure +% this style file is in your TeX search path + + +% This is the LaTeX style file for EACL-95. It is identical to the +% style file for ANLP '94 except that the margins are adjusted for A4 +% paper. -- abney 13 Dec 94 + +% The ANLP '94 style file is a slightly modified +% version of the style used for AAAI and IJCAI, using some changes +% prepared by Fernando Pereira and others and some minor changes +% by Paul Jacobs. + +% Papers prepared using the aclsub.sty file and acl.bst bibtex style +% should be easily converted to final format using this style. +% (1) Submission information (\wordcount, \subject, and \makeidpage) +% should be removed. +% (2) \summary should be removed. The summary material should come +% after \maketitle and should be in the ``abstract'' environment +% (between \begin{abstract} and \end{abstract}). +% (3) Check all citations. This style should handle citations correctly +% and also allows multiple citations separated by semicolons. +% (4) Check figures and examples. Because the final format is double- +% column, some adjustments may have to be made to fit text in the column +% or to choose full-width (\figure*} figures. + +% Place this in a file called aclap.sty in the TeX search path. +% (Placing it in the same directory as the paper should also work.) + +% Prepared by Peter F. Patel-Schneider, liberally using the ideas of +% other style hackers, including Barbara Beeton. +% This style is NOT guaranteed to work. It is provided in the hope +% that it will make the preparation of papers easier. +% +% There are undoubtably bugs in this style. If you make bug fixes, +% improvements, etc. please let me know. My e-mail address is: +% pfps@research.att.com + +% Papers are to be prepared using the ``acl'' bibliography style, +% as follows: +% \documentclass[11pt]{article} +% \usepackage{acl2000} +% \title{Title} +% \author{Author 1 \and Author 2 \\ Address line \\ Address line \And +% Author 3 \\ Address line \\ Address line} +% \begin{document} +% ... +% \bibliography{bibliography-file} +% \bibliographystyle{acl} +% \end{document} + +% Author information can be set in various styles: +% For several authors from the same institution: +% \author{Author 1 \and ... \and Author n \\ +% Address line \\ ... \\ Address line} +% if the names do not fit well on one line use +% Author 1 \\ {\bf Author 2} \\ ... \\ {\bf Author n} \\ +% For authors from different institutions: +% \author{Author 1 \\ Address line \\ ... \\ Address line +% \And ... \And +% Author n \\ Address line \\ ... \\ Address line} +% To start a seperate ``row'' of authors use \AND, as in +% \author{Author 1 \\ Address line \\ ... \\ Address line +% \AND +% Author 2 \\ Address line \\ ... \\ Address line \And +% Author 3 \\ Address line \\ ... \\ Address line} + +% If the title and author information does not fit in the area allocated, +% place \setlength\titlebox{} right after +% \usepackage{acl2000} +% where can be something larger than 2.25in + +% \typeout{Conference Style for ACL 2000 -- released June 20, 2000} +\typeout{Conference Style for ACL 2005 -- released Octobe 11, 2004} + +% NOTE: Some laser printers have a serious problem printing TeX output. +% These printing devices, commonly known as ``write-white'' laser +% printers, tend to make characters too light. To get around this +% problem, a darker set of fonts must be created for these devices. +% + +%% % Physical page layout - slightly modified from IJCAI by pj +%% \setlength\topmargin{0.0in} \setlength\oddsidemargin{-0.0in} +%% \setlength\textheight{9.0in} \setlength\textwidth{6.5in} +%% \setlength\columnsep{0.2in} +%% \newlength\titlebox +%% \setlength\titlebox{2.25in} +%% \setlength\headheight{0pt} \setlength\headsep{0pt} +%% %\setlength\footheight{0pt} +%% \setlength\footskip{0pt} +%% \thispagestyle{empty} \pagestyle{empty} +%% \flushbottom \twocolumn \sloppy + +%% Original A4 version of page layout +%% \setlength\topmargin{-0.45cm} % changed by Rz -1.4 +%% \setlength\oddsidemargin{.8mm} % was -0cm, changed by Rz +%% \setlength\textheight{23.5cm} +%% \setlength\textwidth{15.8cm} +%% \setlength\columnsep{0.6cm} +%% \newlength\titlebox +%% \setlength\titlebox{2.00in} +%% \setlength\headheight{5pt} +%% \setlength\headsep{0pt} +%% \setlength\footheight{0pt} +%% \setlength\footskip{0pt} +%% \thispagestyle{empty} +%% \pagestyle{empty} + +% A4 modified by Eneko +\setlength{\paperwidth}{21cm} % A4 +\setlength{\paperheight}{29.7cm}% A4 +\setlength\topmargin{-0.5cm} +\setlength\oddsidemargin{0cm} +\setlength\textheight{24.7cm} +\setlength\textwidth{16.0cm} +\setlength\columnsep{0.6cm} +\newlength\titlebox +\setlength\titlebox{2.00in} +\setlength\headheight{5pt} +\setlength\headsep{0pt} +\thispagestyle{empty} +\pagestyle{empty} + + +\flushbottom \twocolumn \sloppy + +% We're never going to need a table of contents, so just flush it to +% save space --- suggested by drstrip@sandia-2 +\def\addcontentsline#1#2#3{} + +% Title stuff, taken from deproc. +\def\maketitle{\par + \begingroup + \def\thefootnote{\fnsymbol{footnote}} + \def\@makefnmark{\hbox to 0pt{$^{\@thefnmark}$\hss}} + \twocolumn[\@maketitle] \@thanks + \endgroup + \setcounter{footnote}{0} + \let\maketitle\relax \let\@maketitle\relax + \gdef\@thanks{}\gdef\@author{}\gdef\@title{}\let\thanks\relax} +\def\@maketitle{\vbox to \titlebox{\hsize\textwidth + \linewidth\hsize \vskip 0.125in minus 0.125in \centering + {\Large\bf \@title \par} \vskip 0.2in plus 1fil minus 0.1in + {\def\and{\unskip\enspace{\rm and}\enspace}% + \def\And{\end{tabular}\hss \egroup \hskip 1in plus 2fil + \hbox to 0pt\bgroup\hss \begin{tabular}[t]{c}\bf}% + \def\AND{\end{tabular}\hss\egroup \hfil\hfil\egroup + \vskip 0.25in plus 1fil minus 0.125in + \hbox to \linewidth\bgroup\large \hfil\hfil + \hbox to 0pt\bgroup\hss \begin{tabular}[t]{c}\bf} + \hbox to \linewidth\bgroup\large \hfil\hfil + \hbox to 0pt\bgroup\hss \begin{tabular}[t]{c}\bf\@author + \end{tabular}\hss\egroup + \hfil\hfil\egroup} + \vskip 0.3in plus 2fil minus 0.1in +}} + +% margins for abstract +\renewenvironment{abstract}% + {\centerline{\large\bf Abstract}% + \begin{list}{}% + {\setlength{\rightmargin}{0.6cm}% + \setlength{\leftmargin}{0.6cm}}% + \item[]\ignorespaces}% + {\unskip\end{list}} + +%\renewenvironment{abstract}{\centerline{\large\bf +% Abstract}\vspace{0.5ex}\begin{quote}}{\par\end{quote}\vskip 1ex} + + +% bibliography + +\def\thebibliography#1{\section*{References} + \global\def\@listi{\leftmargin\leftmargini + \labelwidth\leftmargini \advance\labelwidth-\labelsep + \topsep 1pt plus 2pt minus 1pt + \parsep 0.25ex plus 1pt \itemsep 0.25ex plus 1pt} + \list {[\arabic{enumi}]}{\settowidth\labelwidth{[#1]}\leftmargin\labelwidth + \advance\leftmargin\labelsep\usecounter{enumi}} + \def\newblock{\hskip .11em plus .33em minus -.07em} + \sloppy + \sfcode`\.=1000\relax} + +\def\@up#1{\raise.2ex\hbox{#1}} + +% most of cite format is from aclsub.sty by SMS + +% don't box citations, separate with ; and a space +% also, make the penalty between citations negative: a good place to break +% changed comma back to semicolon pj 2/1/90 +% \def\@citex[#1]#2{\if@filesw\immediate\write\@auxout{\string\citation{#2}}\fi +% \def\@citea{}\@cite{\@for\@citeb:=#2\do +% {\@citea\def\@citea{;\penalty\@citeseppen\ }\@ifundefined +% {b@\@citeb}{{\bf ?}\@warning +% {Citation `\@citeb' on page \thepage \space undefined}}% +% {\csname b@\@citeb\endcsname}}}{#1}} + +% don't box citations, separate with ; and a space +% Replaced for multiple citations (pj) +% don't box citations and also add space, semicolon between multiple citations +\def\@citex[#1]#2{\if@filesw\immediate\write\@auxout{\string\citation{#2}}\fi + \def\@citea{}\@cite{\@for\@citeb:=#2\do + {\@citea\def\@citea{; }\@ifundefined + {b@\@citeb}{{\bf ?}\@warning + {Citation `\@citeb' on page \thepage \space undefined}}% + {\csname b@\@citeb\endcsname}}}{#1}} + +% Allow short (name-less) citations, when used in +% conjunction with a bibliography style that creates labels like +% \citename{, } +% +\let\@internalcite\cite +\def\cite{\def\citename##1{##1, }\@internalcite} +\def\shortcite{\def\citename##1{}\@internalcite} +\def\newcite{\def\citename##1{{\frenchspacing##1} (}\@internalciteb} + +% Macros for \newcite, which leaves name in running text, and is +% otherwise like \shortcite. +\def\@citexb[#1]#2{\if@filesw\immediate\write\@auxout{\string\citation{#2}}\fi + \def\@citea{}\@newcite{\@for\@citeb:=#2\do + {\@citea\def\@citea{;\penalty\@m\ }\@ifundefined + {b@\@citeb}{{\bf ?}\@warning + {Citation `\@citeb' on page \thepage \space undefined}}% +{\csname b@\@citeb\endcsname}}}{#1}} +\def\@internalciteb{\@ifnextchar [{\@tempswatrue\@citexb}{\@tempswafalse\@citexb[]}} + +\def\@newcite#1#2{{#1\if@tempswa, #2\fi)}} + +\def\@biblabel#1{\def\citename##1{##1}[#1]\hfill} + +%%% More changes made by SMS (originals in latex.tex) +% Use parentheses instead of square brackets in the text. +\def\@cite#1#2{({#1\if@tempswa , #2\fi})} + +% Don't put a label in the bibliography at all. Just use the unlabeled format +% instead. +\def\thebibliography#1{\vskip\parskip% +\vskip\baselineskip% +\def\baselinestretch{1}% +\ifx\@currsize\normalsize\@normalsize\else\@currsize\fi% +\vskip-\parskip% +\vskip-\baselineskip% +\section*{References\@mkboth + {References}{References}}\list + {}{\setlength{\labelwidth}{0pt}\setlength{\leftmargin}{\parindent} + \setlength{\itemindent}{-\parindent}} + \def\newblock{\hskip .11em plus .33em minus -.07em} + \sloppy\clubpenalty4000\widowpenalty4000 + \sfcode`\.=1000\relax} +\let\endthebibliography=\endlist + +% Allow for a bibliography of sources of attested examples +\def\thesourcebibliography#1{\vskip\parskip% +\vskip\baselineskip% +\def\baselinestretch{1}% +\ifx\@currsize\normalsize\@normalsize\else\@currsize\fi% +\vskip-\parskip% +\vskip-\baselineskip% +\section*{Sources of Attested Examples\@mkboth + {Sources of Attested Examples}{Sources of Attested Examples}}\list + {}{\setlength{\labelwidth}{0pt}\setlength{\leftmargin}{\parindent} + \setlength{\itemindent}{-\parindent}} + \def\newblock{\hskip .11em plus .33em minus -.07em} + \sloppy\clubpenalty4000\widowpenalty4000 + \sfcode`\.=1000\relax} +\let\endthesourcebibliography=\endlist + +\def\@lbibitem[#1]#2{\item[]\if@filesw + { \def\protect##1{\string ##1\space}\immediate + \write\@auxout{\string\bibcite{#2}{#1}}\fi\ignorespaces}} + +\def\@bibitem#1{\item\if@filesw \immediate\write\@auxout + {\string\bibcite{#1}{\the\c@enumi}}\fi\ignorespaces} + +% sections with less space +\def\section{\@startsection {section}{1}{\z@}{-2.0ex plus + -0.5ex minus -.2ex}{1.5ex plus 0.3ex minus .2ex}{\large\bf\raggedright}} +\def\subsection{\@startsection{subsection}{2}{\z@}{-1.8ex plus + -0.5ex minus -.2ex}{0.8ex plus .2ex}{\normalsize\bf\raggedright}} +%% changed by KO to - values to get teh initial parindent right +\def\subsubsection{\@startsection{subsubsection}{3}{\z@}{-1.5ex plus + -0.5ex minus -.2ex}{0.5ex plus .2ex}{\normalsize\bf\raggedright}} +\def\paragraph{\@startsection{paragraph}{4}{\z@}{1.5ex plus + 0.5ex minus .2ex}{-1em}{\normalsize\bf}} +\def\subparagraph{\@startsection{subparagraph}{5}{\parindent}{1.5ex plus + 0.5ex minus .2ex}{-1em}{\normalsize\bf}} + +% Footnotes +\footnotesep 6.65pt % +\skip\footins 9pt plus 4pt minus 2pt +\def\footnoterule{\kern-3pt \hrule width 5pc \kern 2.6pt } +\setcounter{footnote}{0} + +% Lists and paragraphs +\parindent 1em +\topsep 4pt plus 1pt minus 2pt +\partopsep 1pt plus 0.5pt minus 0.5pt +\itemsep 2pt plus 1pt minus 0.5pt +\parsep 2pt plus 1pt minus 0.5pt + +\leftmargin 2em \leftmargini\leftmargin \leftmarginii 2em +\leftmarginiii 1.5em \leftmarginiv 1.0em \leftmarginv .5em \leftmarginvi .5em +\labelwidth\leftmargini\advance\labelwidth-\labelsep \labelsep 5pt + +\def\@listi{\leftmargin\leftmargini} +\def\@listii{\leftmargin\leftmarginii + \labelwidth\leftmarginii\advance\labelwidth-\labelsep + \topsep 2pt plus 1pt minus 0.5pt + \parsep 1pt plus 0.5pt minus 0.5pt + \itemsep \parsep} +\def\@listiii{\leftmargin\leftmarginiii + \labelwidth\leftmarginiii\advance\labelwidth-\labelsep + \topsep 1pt plus 0.5pt minus 0.5pt + \parsep \z@ \partopsep 0.5pt plus 0pt minus 0.5pt + \itemsep \topsep} +\def\@listiv{\leftmargin\leftmarginiv + \labelwidth\leftmarginiv\advance\labelwidth-\labelsep} +\def\@listv{\leftmargin\leftmarginv + \labelwidth\leftmarginv\advance\labelwidth-\labelsep} +\def\@listvi{\leftmargin\leftmarginvi + \labelwidth\leftmarginvi\advance\labelwidth-\labelsep} + +\abovedisplayskip 7pt plus2pt minus5pt% +\belowdisplayskip \abovedisplayskip +\abovedisplayshortskip 0pt plus3pt% +\belowdisplayshortskip 4pt plus3pt minus3pt% + +% Less leading in most fonts (due to the narrow columns) +% The choices were between 1-pt and 1.5-pt leading +\def\@normalsize{\@setsize\normalsize{11pt}\xpt\@xpt} +\def\small{\@setsize\small{10pt}\ixpt\@ixpt} +\def\footnotesize{\@setsize\footnotesize{10pt}\ixpt\@ixpt} +\def\scriptsize{\@setsize\scriptsize{8pt}\viipt\@viipt} +\def\tiny{\@setsize\tiny{7pt}\vipt\@vipt} +\def\large{\@setsize\large{14pt}\xiipt\@xiipt} +\def\Large{\@setsize\Large{16pt}\xivpt\@xivpt} +\def\LARGE{\@setsize\LARGE{20pt}\xviipt\@xviipt} +\def\huge{\@setsize\huge{23pt}\xxpt\@xxpt} +\def\Huge{\@setsize\Huge{28pt}\xxvpt\@xxvpt} diff --git a/papers/2012_emnlp_topic_coherence/acl2012.bst b/papers/2012_emnlp_topic_coherence/acl2012.bst new file mode 100644 index 00000000..26c77653 --- /dev/null +++ b/papers/2012_emnlp_topic_coherence/acl2012.bst @@ -0,0 +1,1322 @@ +% BibTeX `acl' style file for BibTeX version 0.99c, LaTeX version 2.09 +% This version was made by modifying `aaai-named' format based on the master +% file by Oren Patashnik (PATASHNIK@SCORE.STANFORD.EDU) + +% Copyright (C) 1985, all rights reserved. +% Modifications Copyright 1988, Peter F. Patel-Schneider +% Further modifictions by Stuart Shieber, 1991, and Fernando Pereira, 1992. +% Copying of this file is authorized only if either +% (1) you make absolutely no changes to your copy, including name, or +% (2) if you do make changes, you name it something other than +% btxbst.doc, plain.bst, unsrt.bst, alpha.bst, and abbrv.bst. +% This restriction helps ensure that all standard styles are identical. + +% There are undoubtably bugs in this style. If you make bug fixes, +% improvements, etc. please let me know. My e-mail address is: +% pfps@spar.slb.com + +% Citation format: [author-last-name, year] +% [author-last-name and author-last-name, year] +% [author-last-name {\em et al.}, year] +% +% Reference list ordering: alphabetical by author or whatever passes +% for author in the absence of one. +% +% This BibTeX style has support for short (year only) citations. This +% is done by having the citations actually look like +% \citename{name-info, }year +% The LaTeX style has to have the following +% \let\@internalcite\cite +% \def\cite{\def\citename##1{##1}\@internalcite} +% \def\shortcite{\def\citename##1{}\@internalcite} +% \def\@biblabel#1{\def\citename##1{##1}[#1]\hfill} +% which makes \shortcite the macro for short citations. + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% Changes made by SMS for thesis style +% no emphasis on "et al." +% "Ph.D." includes periods (not "PhD") +% moved year to immediately after author's name +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +ENTRY + { address + author + booktitle + chapter + edition + editor + howpublished + institution + journal + key + month + note + number + organization + pages + publisher + school + series + title + type + volume + year + } + {} + { label extra.label sort.label } + +INTEGERS { output.state before.all mid.sentence after.sentence after.block } + +FUNCTION {init.state.consts} +{ #0 'before.all := + #1 'mid.sentence := + #2 'after.sentence := + #3 'after.block := +} + +STRINGS { s t } + +FUNCTION {output.nonnull} +{ 's := + output.state mid.sentence = + { ", " * write$ } + { output.state after.block = + { add.period$ write$ + newline$ + "\newblock " write$ + } + { output.state before.all = + 'write$ + { add.period$ " " * write$ } + if$ + } + if$ + mid.sentence 'output.state := + } + if$ + s +} + +FUNCTION {output} +{ duplicate$ empty$ + 'pop$ + 'output.nonnull + if$ +} + +FUNCTION {output.check} +{ 't := + duplicate$ empty$ + { pop$ "empty " t * " in " * cite$ * warning$ } + 'output.nonnull + if$ +} + +FUNCTION {output.bibitem} +{ newline$ + + "\bibitem[" write$ + label write$ + "]{" write$ + + cite$ write$ + "}" write$ + newline$ + "" + before.all 'output.state := +} + +FUNCTION {fin.entry} +{ add.period$ + write$ + newline$ +} + +FUNCTION {new.block} +{ output.state before.all = + 'skip$ + { after.block 'output.state := } + if$ +} + +FUNCTION {new.sentence} +{ output.state after.block = + 'skip$ + { output.state before.all = + 'skip$ + { after.sentence 'output.state := } + if$ + } + if$ +} + +FUNCTION {not} +{ { #0 } + { #1 } + if$ +} + +FUNCTION {and} +{ 'skip$ + { pop$ #0 } + if$ +} + +FUNCTION {or} +{ { pop$ #1 } + 'skip$ + if$ +} + +FUNCTION {new.block.checka} +{ empty$ + 'skip$ + 'new.block + if$ +} + +FUNCTION {new.block.checkb} +{ empty$ + swap$ empty$ + and + 'skip$ + 'new.block + if$ +} + +FUNCTION {new.sentence.checka} +{ empty$ + 'skip$ + 'new.sentence + if$ +} + +FUNCTION {new.sentence.checkb} +{ empty$ + swap$ empty$ + and + 'skip$ + 'new.sentence + if$ +} + +FUNCTION {field.or.null} +{ duplicate$ empty$ + { pop$ "" } + 'skip$ + if$ +} + +FUNCTION {emphasize} +{ duplicate$ empty$ + { pop$ "" } + { "{\em " swap$ * "}" * } + if$ +} + +INTEGERS { nameptr namesleft numnames } + +FUNCTION {format.names} +{ 's := + #1 'nameptr := + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + + { s nameptr "{ff~}{vv~}{ll}{, jj}" format.name$ 't := + + nameptr #1 > + { namesleft #1 > + { ", " * t * } + { numnames #2 > + { "," * } + 'skip$ + if$ + t "others" = + { " et~al." * } + { " and " * t * } + if$ + } + if$ + } + 't + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {format.authors} +{ author empty$ + { "" } + { author format.names } + if$ +} + +FUNCTION {format.editors} +{ editor empty$ + { "" } + { editor format.names + editor num.names$ #1 > + { ", editors" * } + { ", editor" * } + if$ + } + if$ +} + +FUNCTION {format.title} +{ title empty$ + { "" } + + { title "t" change.case$ } + + if$ +} + +FUNCTION {n.dashify} +{ 't := + "" + { t empty$ not } + { t #1 #1 substring$ "-" = + { t #1 #2 substring$ "--" = not + { "--" * + t #2 global.max$ substring$ 't := + } + { { t #1 #1 substring$ "-" = } + { "-" * + t #2 global.max$ substring$ 't := + } + while$ + } + if$ + } + { t #1 #1 substring$ * + t #2 global.max$ substring$ 't := + } + if$ + } + while$ +} + +FUNCTION {format.date} +{ year empty$ + { month empty$ + { "" } + { "there's a month but no year in " cite$ * warning$ + month + } + if$ + } + { month empty$ + { "" } + { month } + if$ + } + if$ +} + +FUNCTION {format.btitle} +{ title emphasize +} + +FUNCTION {tie.or.space.connect} +{ duplicate$ text.length$ #3 < + { "~" } + { " " } + if$ + swap$ * * +} + +FUNCTION {either.or.check} +{ empty$ + 'pop$ + { "can't use both " swap$ * " fields in " * cite$ * warning$ } + if$ +} + +FUNCTION {format.bvolume} +{ volume empty$ + { "" } + { "volume" volume tie.or.space.connect + series empty$ + 'skip$ + { " of " * series emphasize * } + if$ + "volume and number" number either.or.check + } + if$ +} + +FUNCTION {format.number.series} +{ volume empty$ + { number empty$ + { series field.or.null } + { output.state mid.sentence = + { "number" } + { "Number" } + if$ + number tie.or.space.connect + series empty$ + { "there's a number but no series in " cite$ * warning$ } + { " in " * series * } + if$ + } + if$ + } + { "" } + if$ +} + +FUNCTION {format.edition} +{ edition empty$ + { "" } + { output.state mid.sentence = + { edition "l" change.case$ " edition" * } + { edition "t" change.case$ " edition" * } + if$ + } + if$ +} + +INTEGERS { multiresult } + +FUNCTION {multi.page.check} +{ 't := + #0 'multiresult := + { multiresult not + t empty$ not + and + } + { t #1 #1 substring$ + duplicate$ "-" = + swap$ duplicate$ "," = + swap$ "+" = + or or + { #1 'multiresult := } + { t #2 global.max$ substring$ 't := } + if$ + } + while$ + multiresult +} + +FUNCTION {format.pages} +{ pages empty$ + { "" } + { pages multi.page.check + { "pages" pages n.dashify tie.or.space.connect } + { "page" pages tie.or.space.connect } + if$ + } + if$ +} + +FUNCTION {format.year.label} +{ year extra.label * +} + +FUNCTION {format.vol.num.pages} +{ volume field.or.null + number empty$ + 'skip$ + { "(" number * ")" * * + volume empty$ + { "there's a number but no volume in " cite$ * warning$ } + 'skip$ + if$ + } + if$ + pages empty$ + 'skip$ + { duplicate$ empty$ + { pop$ format.pages } + { ":" * pages n.dashify * } + if$ + } + if$ +} + +FUNCTION {format.chapter.pages} +{ chapter empty$ + 'format.pages + { type empty$ + { "chapter" } + { type "l" change.case$ } + if$ + chapter tie.or.space.connect + pages empty$ + 'skip$ + { ", " * format.pages * } + if$ + } + if$ +} + +FUNCTION {format.in.ed.booktitle} +{ booktitle empty$ + { "" } + { editor empty$ + { "In " booktitle emphasize * } + { "In " format.editors * ", " * booktitle emphasize * } + if$ + } + if$ +} + +FUNCTION {empty.misc.check} +{ author empty$ title empty$ howpublished empty$ + month empty$ year empty$ note empty$ + and and and and and + + key empty$ not and + + { "all relevant fields are empty in " cite$ * warning$ } + 'skip$ + if$ +} + +FUNCTION {format.thesis.type} +{ type empty$ + 'skip$ + { pop$ + type "t" change.case$ + } + if$ +} + +FUNCTION {format.tr.number} +{ type empty$ + { "Technical Report" } + 'type + if$ + number empty$ + { "t" change.case$ } + { number tie.or.space.connect } + if$ +} + +FUNCTION {format.article.crossref} +{ key empty$ + { journal empty$ + { "need key or journal for " cite$ * " to crossref " * crossref * + warning$ + "" + } + { "In {\em " journal * "\/}" * } + if$ + } + { "In " key * } + if$ + " \cite{" * crossref * "}" * +} + +FUNCTION {format.crossref.editor} +{ editor #1 "{vv~}{ll}" format.name$ + editor num.names$ duplicate$ + #2 > + { pop$ " et~al." * } + { #2 < + 'skip$ + { editor #2 "{ff }{vv }{ll}{ jj}" format.name$ "others" = + { " et~al." * } + { " and " * editor #2 "{vv~}{ll}" format.name$ * } + if$ + } + if$ + } + if$ +} + +FUNCTION {format.book.crossref} +{ volume empty$ + { "empty volume in " cite$ * "'s crossref of " * crossref * warning$ + "In " + } + { "Volume" volume tie.or.space.connect + " of " * + } + if$ + editor empty$ + editor field.or.null author field.or.null = + or + { key empty$ + { series empty$ + { "need editor, key, or series for " cite$ * " to crossref " * + crossref * warning$ + "" * + } + { "{\em " * series * "\/}" * } + if$ + } + { key * } + if$ + } + { format.crossref.editor * } + if$ + " \cite{" * crossref * "}" * +} + +FUNCTION {format.incoll.inproc.crossref} +{ editor empty$ + editor field.or.null author field.or.null = + or + { key empty$ + { booktitle empty$ + { "need editor, key, or booktitle for " cite$ * " to crossref " * + crossref * warning$ + "" + } + { "In {\em " booktitle * "\/}" * } + if$ + } + { "In " key * } + if$ + } + { "In " format.crossref.editor * } + if$ + " \cite{" * crossref * "}" * +} + +FUNCTION {article} +{ output.bibitem + format.authors "author" output.check + new.block + format.year.label "year" output.check + new.block + format.title "title" output.check + new.block + crossref missing$ + { journal emphasize "journal" output.check + format.vol.num.pages output + format.date output + } + { format.article.crossref output.nonnull + format.pages output + } + if$ + new.block + note output + fin.entry +} + +FUNCTION {book} +{ output.bibitem + author empty$ + { format.editors "author and editor" output.check } + { format.authors output.nonnull + crossref missing$ + { "author and editor" editor either.or.check } + 'skip$ + if$ + } + if$ + new.block + format.year.label "year" output.check + new.block + format.btitle "title" output.check + crossref missing$ + { format.bvolume output + new.block + format.number.series output + new.sentence + publisher "publisher" output.check + address output + } + { new.block + format.book.crossref output.nonnull + } + if$ + format.edition output + format.date output + new.block + note output + fin.entry +} + +FUNCTION {booklet} +{ output.bibitem + format.authors output + new.block + format.year.label "year" output.check + new.block + format.title "title" output.check + howpublished address new.block.checkb + howpublished output + address output + format.date output + new.block + note output + fin.entry +} + +FUNCTION {inbook} +{ output.bibitem + author empty$ + { format.editors "author and editor" output.check } + { format.authors output.nonnull + crossref missing$ + { "author and editor" editor either.or.check } + 'skip$ + if$ + } + if$ + format.year.label "year" output.check + new.block + new.block + format.btitle "title" output.check + crossref missing$ + { format.bvolume output + format.chapter.pages "chapter and pages" output.check + new.block + format.number.series output + new.sentence + publisher "publisher" output.check + address output + } + { format.chapter.pages "chapter and pages" output.check + new.block + format.book.crossref output.nonnull + } + if$ + format.edition output + format.date output + new.block + note output + fin.entry +} + +FUNCTION {incollection} +{ output.bibitem + format.authors "author" output.check + new.block + format.year.label "year" output.check + new.block + format.title "title" output.check + new.block + crossref missing$ + { format.in.ed.booktitle "booktitle" output.check + format.bvolume output + format.number.series output + format.chapter.pages output + new.sentence + publisher "publisher" output.check + address output + format.edition output + format.date output + } + { format.incoll.inproc.crossref output.nonnull + format.chapter.pages output + } + if$ + new.block + note output + fin.entry +} + +FUNCTION {inproceedings} +{ output.bibitem + format.authors "author" output.check + new.block + format.year.label "year" output.check + new.block + format.title "title" output.check + new.block + crossref missing$ + { format.in.ed.booktitle "booktitle" output.check + format.bvolume output + format.number.series output + format.pages output + address empty$ + { organization publisher new.sentence.checkb + organization output + publisher output + format.date output + } + { address output.nonnull + format.date output + new.sentence + organization output + publisher output + } + if$ + } + { format.incoll.inproc.crossref output.nonnull + format.pages output + } + if$ + new.block + note output + fin.entry +} + +FUNCTION {conference} { inproceedings } + +FUNCTION {manual} +{ output.bibitem + author empty$ + { organization empty$ + 'skip$ + { organization output.nonnull + address output + } + if$ + } + { format.authors output.nonnull } + if$ + format.year.label "year" output.check + new.block + new.block + format.btitle "title" output.check + author empty$ + { organization empty$ + { address new.block.checka + address output + } + 'skip$ + if$ + } + { organization address new.block.checkb + organization output + address output + } + if$ + format.edition output + format.date output + new.block + note output + fin.entry +} + +FUNCTION {mastersthesis} +{ output.bibitem + format.authors "author" output.check + new.block + format.year.label "year" output.check + new.block + format.title "title" output.check + new.block + "Master's thesis" format.thesis.type output.nonnull + school "school" output.check + address output + format.date output + new.block + note output + fin.entry +} + +FUNCTION {misc} +{ output.bibitem + format.authors output + new.block + format.year.label output + new.block + title howpublished new.block.checkb + format.title output + howpublished new.block.checka + howpublished output + format.date output + new.block + note output + fin.entry + empty.misc.check +} + +FUNCTION {phdthesis} +{ output.bibitem + format.authors "author" output.check + new.block + format.year.label "year" output.check + new.block + format.btitle "title" output.check + new.block + "{Ph.D.} thesis" format.thesis.type output.nonnull + school "school" output.check + address output + format.date output + new.block + note output + fin.entry +} + +FUNCTION {proceedings} +{ output.bibitem + editor empty$ + { organization output } + { format.editors output.nonnull } + if$ + new.block + format.year.label "year" output.check + new.block + format.btitle "title" output.check + format.bvolume output + format.number.series output + address empty$ + { editor empty$ + { publisher new.sentence.checka } + { organization publisher new.sentence.checkb + organization output + } + if$ + publisher output + format.date output + } + { address output.nonnull + format.date output + new.sentence + editor empty$ + 'skip$ + { organization output } + if$ + publisher output + } + if$ + new.block + note output + fin.entry +} + +FUNCTION {techreport} +{ output.bibitem + format.authors "author" output.check + new.block + format.year.label "year" output.check + new.block + format.title "title" output.check + new.block + format.tr.number output.nonnull + institution "institution" output.check + address output + format.date output + new.block + note output + fin.entry +} + +FUNCTION {unpublished} +{ output.bibitem + format.authors "author" output.check + new.block + format.year.label "year" output.check + new.block + format.title "title" output.check + new.block + note "note" output.check + format.date output + fin.entry +} + +FUNCTION {default.type} { misc } + +MACRO {jan} {"January"} + +MACRO {feb} {"February"} + +MACRO {mar} {"March"} + +MACRO {apr} {"April"} + +MACRO {may} {"May"} + +MACRO {jun} {"June"} + +MACRO {jul} {"July"} + +MACRO {aug} {"August"} + +MACRO {sep} {"September"} + +MACRO {oct} {"October"} + +MACRO {nov} {"November"} + +MACRO {dec} {"December"} + +MACRO {acmcs} {"ACM Computing Surveys"} + +MACRO {acta} {"Acta Informatica"} + +MACRO {cacm} {"Communications of the ACM"} + +MACRO {ibmjrd} {"IBM Journal of Research and Development"} + +MACRO {ibmsj} {"IBM Systems Journal"} + +MACRO {ieeese} {"IEEE Transactions on Software Engineering"} + +MACRO {ieeetc} {"IEEE Transactions on Computers"} + +MACRO {ieeetcad} + {"IEEE Transactions on Computer-Aided Design of Integrated Circuits"} + +MACRO {ipl} {"Information Processing Letters"} + +MACRO {jacm} {"Journal of the ACM"} + +MACRO {jcss} {"Journal of Computer and System Sciences"} + +MACRO {scp} {"Science of Computer Programming"} + +MACRO {sicomp} {"SIAM Journal on Computing"} + +MACRO {tocs} {"ACM Transactions on Computer Systems"} + +MACRO {tods} {"ACM Transactions on Database Systems"} + +MACRO {tog} {"ACM Transactions on Graphics"} + +MACRO {toms} {"ACM Transactions on Mathematical Software"} + +MACRO {toois} {"ACM Transactions on Office Information Systems"} + +MACRO {toplas} {"ACM Transactions on Programming Languages and Systems"} + +MACRO {tcs} {"Theoretical Computer Science"} + +READ + +FUNCTION {sortify} +{ purify$ + "l" change.case$ +} + +INTEGERS { len } + +FUNCTION {chop.word} +{ 's := + 'len := + s #1 len substring$ = + { s len #1 + global.max$ substring$ } + 's + if$ +} + +INTEGERS { et.al.char.used } + +FUNCTION {initialize.et.al.char.used} +{ #0 'et.al.char.used := +} + +EXECUTE {initialize.et.al.char.used} + +FUNCTION {format.lab.names} +{ 's := + s num.names$ 'numnames := + + numnames #1 = + { s #1 "{vv }{ll}" format.name$ } + { numnames #2 = + { s #1 "{vv }{ll }and " format.name$ s #2 "{vv }{ll}" format.name$ * + } + { s #1 "{vv }{ll }\bgroup et al.\egroup " format.name$ } + if$ + } + if$ + +} + +FUNCTION {author.key.label} +{ author empty$ + { key empty$ + + { cite$ #1 #3 substring$ } + + { key #3 text.prefix$ } + if$ + } + { author format.lab.names } + if$ +} + +FUNCTION {author.editor.key.label} +{ author empty$ + { editor empty$ + { key empty$ + + { cite$ #1 #3 substring$ } + + { key #3 text.prefix$ } + if$ + } + { editor format.lab.names } + if$ + } + { author format.lab.names } + if$ +} + +FUNCTION {author.key.organization.label} +{ author empty$ + { key empty$ + { organization empty$ + + { cite$ #1 #3 substring$ } + + { "The " #4 organization chop.word #3 text.prefix$ } + if$ + } + { key #3 text.prefix$ } + if$ + } + { author format.lab.names } + if$ +} + +FUNCTION {editor.key.organization.label} +{ editor empty$ + { key empty$ + { organization empty$ + + { cite$ #1 #3 substring$ } + + { "The " #4 organization chop.word #3 text.prefix$ } + if$ + } + { key #3 text.prefix$ } + if$ + } + { editor format.lab.names } + if$ +} + +FUNCTION {calc.label} +{ type$ "book" = + type$ "inbook" = + or + 'author.editor.key.label + { type$ "proceedings" = + 'editor.key.organization.label + { type$ "manual" = + 'author.key.organization.label + 'author.key.label + if$ + } + if$ + } + if$ + duplicate$ + + "\protect\citename{" swap$ * "}" * + year field.or.null purify$ * + 'label := + year field.or.null purify$ * + + sortify 'sort.label := +} + +FUNCTION {sort.format.names} +{ 's := + #1 'nameptr := + "" + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + { nameptr #1 > + { " " * } + 'skip$ + if$ + + s nameptr "{vv{ } }{ll{ }}{ ff{ }}{ jj{ }}" format.name$ 't := + + nameptr numnames = t "others" = and + { "et al" * } + { t sortify * } + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {sort.format.title} +{ 't := + "A " #2 + "An " #3 + "The " #4 t chop.word + chop.word + chop.word + sortify + #1 global.max$ substring$ +} + +FUNCTION {author.sort} +{ author empty$ + { key empty$ + { "to sort, need author or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { author sort.format.names } + if$ +} + +FUNCTION {author.editor.sort} +{ author empty$ + { editor empty$ + { key empty$ + { "to sort, need author, editor, or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { editor sort.format.names } + if$ + } + { author sort.format.names } + if$ +} + +FUNCTION {author.organization.sort} +{ author empty$ + { organization empty$ + { key empty$ + { "to sort, need author, organization, or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { "The " #4 organization chop.word sortify } + if$ + } + { author sort.format.names } + if$ +} + +FUNCTION {editor.organization.sort} +{ editor empty$ + { organization empty$ + { key empty$ + { "to sort, need editor, organization, or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { "The " #4 organization chop.word sortify } + if$ + } + { editor sort.format.names } + if$ +} + +FUNCTION {presort} + +{ calc.label + sort.label + " " + * + type$ "book" = + + type$ "inbook" = + or + 'author.editor.sort + { type$ "proceedings" = + 'editor.organization.sort + { type$ "manual" = + 'author.organization.sort + 'author.sort + if$ + } + if$ + } + if$ + + * + + " " + * + year field.or.null sortify + * + " " + * + title field.or.null + sort.format.title + * + #1 entry.max$ substring$ + 'sort.key$ := +} + +ITERATE {presort} + +SORT + +STRINGS { longest.label last.sort.label next.extra } + +INTEGERS { longest.label.width last.extra.num } + +FUNCTION {initialize.longest.label} +{ "" 'longest.label := + #0 int.to.chr$ 'last.sort.label := + "" 'next.extra := + #0 'longest.label.width := + #0 'last.extra.num := +} + +FUNCTION {forward.pass} +{ last.sort.label sort.label = + { last.extra.num #1 + 'last.extra.num := + last.extra.num int.to.chr$ 'extra.label := + } + { "a" chr.to.int$ 'last.extra.num := + "" 'extra.label := + sort.label 'last.sort.label := + } + if$ +} + +FUNCTION {reverse.pass} +{ next.extra "b" = + { "a" 'extra.label := } + 'skip$ + if$ + label extra.label * 'label := + label width$ longest.label.width > + { label 'longest.label := + label width$ 'longest.label.width := + } + 'skip$ + if$ + extra.label 'next.extra := +} + +EXECUTE {initialize.longest.label} + +ITERATE {forward.pass} + +REVERSE {reverse.pass} + +FUNCTION {begin.bib} + +{ et.al.char.used + { "\newcommand{\etalchar}[1]{$^{#1}$}" write$ newline$ } + 'skip$ + if$ + preamble$ empty$ + + 'skip$ + { preamble$ write$ newline$ } + if$ + + "\begin{thebibliography}{" "}" * write$ newline$ + +} + +EXECUTE {begin.bib} + +EXECUTE {init.state.consts} + +ITERATE {call.type$} + +FUNCTION {end.bib} +{ newline$ + "\end{thebibliography}" write$ newline$ +} + +EXECUTE {end.bib} + + diff --git a/papers/2012_emnlp_topic_coherence/acl2012.sty b/papers/2012_emnlp_topic_coherence/acl2012.sty new file mode 100644 index 00000000..4fe75535 --- /dev/null +++ b/papers/2012_emnlp_topic_coherence/acl2012.sty @@ -0,0 +1,343 @@ +% File acl2012.sty +% October 11, 2004 +% Contact: oflazer@sabanciuniv.edu + +% This is the LaTeX style file for ACL 2005. It is nearly identical to the +% style files for ACL 2002, ACL 2001, ACL 2000, EACL 95 and EACL +% 99. +% +% This is the LaTeX style file for ACL 2000. It is nearly identical to the +% style files for EACL 95 and EACL 99. Minor changes include editing the +% instructions to reflect use of \documentclass rather than \documentstyle +% and removing the white space before the title on the first page +% -- John Chen, June 29, 2000 + +% To convert from submissions prepared using the style file aclsub.sty +% prepared for the ACL 2000 conference, proceed as follows: +% 1) Remove submission-specific information: \whichsession, \id, +% \wordcount, \otherconferences, \area, \keywords +% 2) \summary should be removed. The summary material should come +% after \maketitle and should be in the ``abstract'' environment +% 3) Check all citations. This style should handle citations correctly +% and also allows multiple citations separated by semicolons. +% 4) Check figures and examples. Because the final format is double- +% column, some adjustments may have to be made to fit text in the column +% or to choose full-width (\figure*} figures. +% 5) Change the style reference from aclsub to acl2000, and be sure +% this style file is in your TeX search path + + +% This is the LaTeX style file for EACL-95. It is identical to the +% style file for ANLP '94 except that the margins are adjusted for A4 +% paper. -- abney 13 Dec 94 + +% The ANLP '94 style file is a slightly modified +% version of the style used for AAAI and IJCAI, using some changes +% prepared by Fernando Pereira and others and some minor changes +% by Paul Jacobs. + +% Papers prepared using the aclsub.sty file and acl.bst bibtex style +% should be easily converted to final format using this style. +% (1) Submission information (\wordcount, \subject, and \makeidpage) +% should be removed. +% (2) \summary should be removed. The summary material should come +% after \maketitle and should be in the ``abstract'' environment +% (between \begin{abstract} and \end{abstract}). +% (3) Check all citations. This style should handle citations correctly +% and also allows multiple citations separated by semicolons. +% (4) Check figures and examples. Because the final format is double- +% column, some adjustments may have to be made to fit text in the column +% or to choose full-width (\figure*} figures. + +% Place this in a file called aclap.sty in the TeX search path. +% (Placing it in the same directory as the paper should also work.) + +% Prepared by Peter F. Patel-Schneider, liberally using the ideas of +% other style hackers, including Barbara Beeton. +% This style is NOT guaranteed to work. It is provided in the hope +% that it will make the preparation of papers easier. +% +% There are undoubtably bugs in this style. If you make bug fixes, +% improvements, etc. please let me know. My e-mail address is: +% pfps@research.att.com + +% Papers are to be prepared using the ``acl'' bibliography style, +% as follows: +% \documentclass[11pt]{article} +% \usepackage{acl2000} +% \title{Title} +% \author{Author 1 \and Author 2 \\ Address line \\ Address line \And +% Author 3 \\ Address line \\ Address line} +% \begin{document} +% ... +% \bibliography{bibliography-file} +% \bibliographystyle{acl} +% \end{document} + +% Author information can be set in various styles: +% For several authors from the same institution: +% \author{Author 1 \and ... \and Author n \\ +% Address line \\ ... \\ Address line} +% if the names do not fit well on one line use +% Author 1 \\ {\bf Author 2} \\ ... \\ {\bf Author n} \\ +% For authors from different institutions: +% \author{Author 1 \\ Address line \\ ... \\ Address line +% \And ... \And +% Author n \\ Address line \\ ... \\ Address line} +% To start a seperate ``row'' of authors use \AND, as in +% \author{Author 1 \\ Address line \\ ... \\ Address line +% \AND +% Author 2 \\ Address line \\ ... \\ Address line \And +% Author 3 \\ Address line \\ ... \\ Address line} + +% If the title and author information does not fit in the area allocated, +% place \setlength\titlebox{} right after +% \usepackage{acl2000} +% where can be something larger than 2.25in + +% \typeout{Conference Style for ACL 2000 -- released June 20, 2000} +\typeout{Conference Style for ACL 2005 -- released Octobe 11, 2004} + +% NOTE: Some laser printers have a serious problem printing TeX output. +% These printing devices, commonly known as ``write-white'' laser +% printers, tend to make characters too light. To get around this +% problem, a darker set of fonts must be created for these devices. +% + +% Physical page layout - slightly modified from IJCAI by pj +\setlength\topmargin{0.0in} \setlength\oddsidemargin{-0.0in} +\setlength\textheight{9.0in} \setlength\textwidth{6.5in} +\setlength\columnsep{0.2in} +\newlength\titlebox +\setlength\titlebox{2.25in} +\setlength\headheight{0pt} \setlength\headsep{0pt} +%\setlength\footheight{0pt} +\setlength\footskip{0pt} +\thispagestyle{empty} \pagestyle{empty} +\flushbottom \twocolumn \sloppy + +%% A4 version of page layout +%\setlength\topmargin{-0.45cm} % changed by Rz -1.4 +%\setlength\oddsidemargin{.8mm} % was -0cm, changed by Rz +%\setlength\textheight{23.5cm} +%\setlength\textwidth{15.8cm} +%\setlength\columnsep{0.6cm} +%\newlength\titlebox +%\setlength\titlebox{2.00in} +%\setlength\headheight{5pt} +%\setlength\headsep{0pt} +%%\setlength\footheight{0pt} +%\setlength\footskip{0pt} +%\thispagestyle{empty} +%\pagestyle{empty} + +\flushbottom \twocolumn \sloppy + +% We're never going to need a table of contents, so just flush it to +% save space --- suggested by drstrip@sandia-2 +\def\addcontentsline#1#2#3{} + +% Title stuff, taken from deproc. +\def\maketitle{\par + \begingroup + \def\thefootnote{\fnsymbol{footnote}} + \def\@makefnmark{\hbox to 0pt{$^{\@thefnmark}$\hss}} + \twocolumn[\@maketitle] \@thanks + \endgroup + \setcounter{footnote}{0} + \let\maketitle\relax \let\@maketitle\relax + \gdef\@thanks{}\gdef\@author{}\gdef\@title{}\let\thanks\relax} +\def\@maketitle{\vbox to \titlebox{\hsize\textwidth + \linewidth\hsize \vskip 0.125in minus 0.125in \centering + {\Large\bf \@title \par} \vskip 0.2in plus 1fil minus 0.1in + {\def\and{\unskip\enspace{\rm and}\enspace}% + \def\And{\end{tabular}\hss \egroup \hskip 1in plus 2fil + \hbox to 0pt\bgroup\hss \begin{tabular}[t]{c}\bf}% + \def\AND{\end{tabular}\hss\egroup \hfil\hfil\egroup + \vskip 0.25in plus 1fil minus 0.125in + \hbox to \linewidth\bgroup\large \hfil\hfil + \hbox to 0pt\bgroup\hss \begin{tabular}[t]{c}\bf} + \hbox to \linewidth\bgroup\large \hfil\hfil + \hbox to 0pt\bgroup\hss \begin{tabular}[t]{c}\bf\@author + \end{tabular}\hss\egroup + \hfil\hfil\egroup} + \vskip 0.3in plus 2fil minus 0.1in +}} +\renewenvironment{abstract}{\centerline{\large\bf + Abstract}\vspace{0.5ex}\begin{quote} \small}{\par\end{quote}\vskip 1ex} + + +% bibliography + +\def\thebibliography#1{\section*{References} + \global\def\@listi{\leftmargin\leftmargini + \labelwidth\leftmargini \advance\labelwidth-\labelsep + \topsep 1pt plus 2pt minus 1pt + \parsep 0.25ex plus 1pt \itemsep 0.25ex plus 1pt} + \list {[\arabic{enumi}]}{\settowidth\labelwidth{[#1]}\leftmargin\labelwidth + \advance\leftmargin\labelsep\usecounter{enumi}} + \def\newblock{\hskip .11em plus .33em minus -.07em} + \sloppy + \sfcode`\.=1000\relax} + +\def\@up#1{\raise.2ex\hbox{#1}} + +% most of cite format is from aclsub.sty by SMS + +% don't box citations, separate with ; and a space +% also, make the penalty between citations negative: a good place to break +% changed comma back to semicolon pj 2/1/90 +% \def\@citex[#1]#2{\if@filesw\immediate\write\@auxout{\string\citation{#2}}\fi +% \def\@citea{}\@cite{\@for\@citeb:=#2\do +% {\@citea\def\@citea{;\penalty\@citeseppen\ }\@ifundefined +% {b@\@citeb}{{\bf ?}\@warning +% {Citation `\@citeb' on page \thepage \space undefined}}% +% {\csname b@\@citeb\endcsname}}}{#1}} + +% don't box citations, separate with ; and a space +% Replaced for multiple citations (pj) +% don't box citations and also add space, semicolon between multiple citations +\def\@citex[#1]#2{\if@filesw\immediate\write\@auxout{\string\citation{#2}}\fi + \def\@citea{}\@cite{\@for\@citeb:=#2\do + {\@citea\def\@citea{; }\@ifundefined + {b@\@citeb}{{\bf ?}\@warning + {Citation `\@citeb' on page \thepage \space undefined}}% + {\csname b@\@citeb\endcsname}}}{#1}} + +% Allow short (name-less) citations, when used in +% conjunction with a bibliography style that creates labels like +% \citename{, } +% +\let\@internalcite\cite +\def\cite{\def\citename##1{##1, }\@internalcite} +\def\shortcite{\def\citename##1{}\@internalcite} +\def\newcite{\def\citename##1{{\frenchspacing##1} (}\@internalciteb} + +% Macros for \newcite, which leaves name in running text, and is +% otherwise like \shortcite. +\def\@citexb[#1]#2{\if@filesw\immediate\write\@auxout{\string\citation{#2}}\fi + \def\@citea{}\@newcite{\@for\@citeb:=#2\do + {\@citea\def\@citea{;\penalty\@m\ }\@ifundefined + {b@\@citeb}{{\bf ?}\@warning + {Citation `\@citeb' on page \thepage \space undefined}}% +{\csname b@\@citeb\endcsname}}}{#1}} +\def\@internalciteb{\@ifnextchar [{\@tempswatrue\@citexb}{\@tempswafalse\@citexb[]}} + +\def\@newcite#1#2{{#1\if@tempswa, #2\fi)}} + +\def\@biblabel#1{\def\citename##1{##1}[#1]\hfill} + +%%% More changes made by SMS (originals in latex.tex) +% Use parentheses instead of square brackets in the text. +\def\@cite#1#2{({#1\if@tempswa , #2\fi})} + +% Don't put a label in the bibliography at all. 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These measurements help +distinguish between topics that are semantically interpretable topics and topics +that are artifacts of statistical inference, see Table \ref{tab:best} for +examples ordered by the UCI measure. For our evaluations, we consider two new +coherence measures designed for LDA, both of which have been shown to match well +with human judgements of topic quality: (1) The UCI measure \cite{newman10uci} +and (2) The UMass measure \cite{mimno11umass}. + +Both measures compute the coherence of a topic as the +sum of pairwise distributional similarity scores over the set of topic +words, $V$. We generalize this as + +$$coherence(V) = \sum_{(v_i, v_j) \in V} score(v_i, v_j, \epsilon)$$ +\noindent +where $V$ is a set of word describing the topic and $\epsilon$ indicates a +smoothing factor which guarantees that $score$ returns real numbers. +(We will be exploring the effect of the choice of $\epsilon$; the +original authors used $\epsilon=1$.) + +\paragraph{The UCI metric} defines a word pair's score to be the pointwise +mutual information (PMI) between two words, i.e. + +$$score(v_i,v_j,\epsilon) = \log \frac{p(v_i, v_j) + \epsilon}{p(v_i)p(v_j)}$$ +\noindent +The word probabilities are computed by counting word co-occurrence frequencies +in a sliding window over an external corpus, such as Wikipedia. To some degree, +this metric can be thought of as an external comparison to known semantic +evaluations. + +\begin{figure*}[h!t!b!] + \centering + \subfloat[UMass]{\label{fig:mean-umass}\includegraphics[width=.50\textwidth,height=.35\textwidth]{plots/mean-umass.eps}} + \subfloat[UCI]{\label{fig:mean-uci}\includegraphics[width=.50\textwidth,height=.35\textwidth]{plots/mean-uci.eps}} + \caption{Average Topic Coherence for each model} + \label{fig:mean} +\end{figure*} + +\begin{figure*}[h!t!b!] + \centering + \subfloat[UMass]{\label{fig:entropy-umass}\includegraphics[width=.50\textwidth,height=.35\textwidth]{plots/entropy-umassNoLog.eps}} + \subfloat[UCI]{\label{fig:entropy-uci}\includegraphics[width=.50\textwidth,height=.35\textwidth]{plots/entropy-uciNoLog.eps}} + \caption{Entropy of the Topic Coherence for each model} + \label{fig:entropy} +\end{figure*} + +\paragraph{The UMass metric} defines the score to be based on document co-occurrence: + +$$score(v_i, v_j,\epsilon) = \log \frac{D(v_i, v_j) + \epsilon}{D(v_j)}$$ +\noindent +where $D(x,y)$ counts the number of documents containing words $x$ and $y$ and +$D(x)$ counts the number of documents containing $x$. Significantly, the UMass +metric computes these counts over the \textit{original corpus} used to train the +topic models, rather than an external corpus. This metric is more intrinsic in +nature. It attempts to confirm that the models learned data known to be in the +corpus. diff --git a/papers/2012_emnlp_topic_coherence/discussion.tex b/papers/2012_emnlp_topic_coherence/discussion.tex new file mode 100644 index 00000000..f56d02c0 --- /dev/null +++ b/papers/2012_emnlp_topic_coherence/discussion.tex @@ -0,0 +1,41 @@ +\label{sec:discusssion} +Through our experiments, we made several exciting and interesting discoveries. +First, we discovered that the coherence metrics depend heavily on the smoothing +factor $\epsilon$. The original value, $1.0$ created a positive bias towards +NMF from both metrics even when NMF generated incoherent topics. The high +smoothing factor also gave a significant increase to SVD scores. We suspect +that this was not an issue in previous studies with the coherence measures as +LDA prefers to form topics from words that co-occur frequently, whereas NMF and +SVD have no such preferences and often create low quality topics from completely +unrelated words. Therefore, we suggest a smaller $\epsilon$ value in general. + +We also found that the UCI measure often agreed with the UMass measure, but the +UCI-entropy aggregate method induced more separation between LSA, SVD, and NMF +in terms of topic coherence. This measure also revealed the importance of the +smoothing factor for topic coherence measures. + +With respects to human judgements, we found that coherence scores do not always +indicate a better representation of distributional information. The SVD model +consistently out performed both LDA and NMF models, which each had higher +coherence scores, when attempting to predict human judgements of similarity. + +Lastly, we found all models capable of producing topics that improved document +classification. At the same time, SVD provided the most information during +classification and outperformed the other models, which again had more coherent +topics. Our comparison between topic coherence scores and feature importance in +classification revealed that relatively high quality topics, but not the most +coherent topics, drive most of the classification decisions, and most topics do +not affect the accuracy. + +Overall, we see that each topic model paradigm has it's own strengths and +weaknesses. Latent Semantic Analysis with Singular Value Decomposition fails to +form individual topics that aggregate similar words, but it does remarkably well +when considering all the learned topics as similar words develop a similar topic +representation. These topics similarly perform well during classification. +Conversely, both Non Negative Matrix factorization and Latent Dirichlet +Allocation learn concise and coherent topics and achieved similar performance on +our evaluations. However, NMF learns more incoherent topics than LDA and SVD. +For applications in which a human end-user will interact with learned topics, +the flexibility of LDA and the coherence advantages of LDA warrant strong +consideration. All of code for this work will be made available through an open +source project.\footnote{https://github.com/fozziethebeat/TopicModelComparison} diff --git a/papers/2012_emnlp_topic_coherence/evaluation.tex b/papers/2012_emnlp_topic_coherence/evaluation.tex new file mode 100644 index 00000000..b042f031 --- /dev/null +++ b/papers/2012_emnlp_topic_coherence/evaluation.tex @@ -0,0 +1,323 @@ +\label{sec:evaluation} +We evaluate the quality of our three topic models (LDA, SVD, and NMF) with three +experiments. We focus first on evaluating aggregate coherence methods for a complete +topic model and consider the differences between each model as we learn an +increasing number of topics. Secondly, we compare coherence scores to previous +semantic evaluations. Lastly, we use the learned topics in a classification +task and evaluate whether or not coherent topics are equally informative when +discriminating between documents. + +For all our experiments, we trained our models on 92,600 New York Times articles +from 2003 \cite{nytcorpus}. For all articles, we removed stop words and any +words occurring less than 200 times in the corpus, which left 35,836 unique +tokens. All documents were tokenized with OpenNLP's +MaxEnt\footnote{http://incubator.apache.org/opennlp/} tokenizer. For the UCI +measure, we compute the PMI between words using a 20 word sliding window passed +over the WaCkypedia corpus \cite{baroni09wacky}. In all experiments, we compute +the coherence with the top 10 words from each topic that had the highest weight, +in terms of LDA and NMF this corresponds with a high probability of the term +describing the topic but for SVD there is no clear semantic interpretation. + +\subsection{Aggregate methods for topic coherence} + +\begin{figure*}[h!t!b!] + \centering + \subfloat[UMass]{\label{fig:mean-umassNoSmooth}\includegraphics[width=.50\textwidth,height=.35\textwidth]{plots/mean-umassNoSmoothing.eps}} + \subfloat[UCI]{\label{fig:mean-uciNoSmooth}\includegraphics[width=.50\textwidth,height=.35\textwidth]{plots/mean-uciNoSmoothing.eps}} + \caption{Average Topic Coherence with $\epsilon=10^{-12}$} + \label{fig:mean-smoothing} +\end{figure*} + +\begin{figure*}[h!t!b!] + \centering + \subfloat[UMass]{\label{fig:10mean-umassNoSmooth}\includegraphics[width=.50\textwidth,height=.35\textwidth]{plots/10mean-umassNoSmoothing.eps}} + \subfloat[UCI]{\label{fig:10mean-uciNoSmooth}\includegraphics[width=.50\textwidth,height=.35\textwidth]{plots/10mean-uciNoSmoothing.eps}} + \caption{Average Topic Coherence of the top 10\% topics with $\epsilon=10^{-12}$} + \label{fig:10mean-smoothing} +\end{figure*} + +Before we can compare topic models, we require an aggregate +measure that represents the quality of a complete model, +rather than individual topics. We consider two aggregates methods: +(1) the average coherence of all topics and +(2) the entropy of the coherence for all topics. +The average coherence provides a quick summarization of a model's quality +whereas the entropy provides an alternate summarization that differentiates +between two interesting situations. Since entropy measures the complexity of a +probability distribution, it can easily differentiate between uniform +distributions and multimodal, distributions. This distinction is relevant when +users prefer to have roughly uniform topic quality instead of a wide gap between +high- and low-quality topics, or vice versa. We compute the entropy by dropping +the $log$ and $\epsilon$ factor from each scoring function. + +Figure \ref{fig:mean} shows the average coherence scores for each model as we +vary the number of topics. These average scores indicate some simple +relationships between the models: LDA and NMF have approximately the same +performance and both models are consistently better than SVD. All of the models +quickly reach a stable average score at around 100 topics. This initially +suggests that learning more topics neither increases or decreases the quality of +the model, but Figure \ref{fig:entropy} indicates otherwise. While the entropy +for the UMass score stays stable for all models, NMF produces erratic entropy +results under the UCI score as we learn more topics. As entropy is higher for +even distributions and lower for all other distributions, these results suggest +that the NMF is learning topics with drastically different levels of quality, +i.e. some with high quality and some with very low quality, but the average +coherence over all topics do not account for this. + +\begin{comment} +\begin{figure*}[h!t!b!] + \centering + \subfloat[UMass]{\label{fig:ordered-umassNoSmooth}\includegraphics[width=.50\textwidth,height=.35\textwidth]{plots/lda-nmf-umass.eps}} + \subfloat[UCI]{\label{fig:ordered-uciNoSmooth}\includegraphics[width=.50\textwidth,height=.35\textwidth]{plots/lda-nmf-uci.eps}} + \caption{Bipartite weights between LDA and NMF models using the Hungarian Algorithm} + \label{fig:paired-weights} +\end{figure*} + +\begin{figure*}[h!t!b!] + \centering + \subfloat[UMass]{\label{fig:ordered-umassNoSmooth}\includegraphics[width=.50\textwidth,height=.35\textwidth]{plots/lda-nmf-umass-300.eps}} + \subfloat[UCI]{\label{fig:ordered-uciNoSmooth}\includegraphics[width=.50\textwidth,height=.35\textwidth]{plots/lda-nmf-uci-300.eps}} + \caption{Relation between bipartite weights and topic coherence scores for 300 topics} + \label{fig:score-weight-300} +\end{figure*} +\end{comment} + +\begin{figure*}[h!t!b!] + \centering + \subfloat[Rubenstein \& + Goodenough]{\label{fig:rng-wordsim}\includegraphics[width=.50\textwidth,height=.35\textwidth]{plots/rng_wordsim.eps}} + \subfloat[Wordsim + 353/Finklestein~et.~al.]{\label{fig:353-wordsim}\includegraphics[width=.50\textwidth,height=.35\textwidth]{plots/353_wordsim.eps}} + \caption{Word Similarity Evaluations for each model} + \label{fig:wordsim} +\end{figure*} + +\begin{figure}[h!t!b!] + \centering + \includegraphics[width=.50\textwidth,height=.35\textwidth]{plots/avatar_classifier.eps} + \caption{Classification accuracy for each model} + \label{fig:predict} +\end{figure} + +Low quality topics may be composed of highly unrelated words that +can't be fit into another topic, and in this case, our smoothing +factor, $\epsilon$, may be artificially increasing the score for +unrelated words. Following the practice of the original use of these +metrics, in Figures~\ref{fig:mean} and \ref{fig:entropy} we set +$\epsilon = 1$. In Figure~\ref{fig:mean-smoothing}, we consider +$\epsilon = 10^{-12}$, which should significantly reduce the score for +completely unrelated words. Here, we see a significant change in the +performance of NMF, the average coherence decreases dramatically as we +learn more topics. Similarly, performance of SVD drops dramatically +and well below the other models. In figure \ref{fig:10mean-smoothing} +we lastly compute the average coherence using only the top 10\% most +coherence topics with $\epsilon = 10^{-12}$. Here, NMF again performs +on par with LDA. With the top 10\% topics still having a high average +coherence but the full set of topics having a low coherence, NMF +appears to be learning more low quality topics once it's learned the +first 100 topics, whereas LDA learns fewer low quality topics in +general. + +\begin{comment} +\begin{figure*} + \centering + \subfloat[UMass]{\label{fig:ordered-umass}\includegraphics[width=.50\textwidth,height=.35\textwidth]{plots/ordered_300_umass.eps}} + \subfloat[UCI]{\label{fig:ordered-uci}\includegraphics[width=.50\textwidth,height=.35\textwidth]{plots/ordered_300_uci.eps}} + \caption{Topic Coherence for the top X\% topics out of 300 topics} + \label{fig:top10avg} +\end{figure*} + +\begin{figure*} + \centering + \subfloat[UMass]{\label{fig:ordered-umassNoSmooth}\includegraphics[width=.50\textwidth,height=.35\textwidth]{plots/ordered_300_umassNoSmoothing.eps}} + \subfloat[UCI]{\label{fig:ordered-uciNoSmooth}\includegraphics[width=.50\textwidth,height=.35\textwidth]{plots/ordered_300_uciNoSmoothing.eps}} + \caption{Topic Coherence for the top X\% topics out of 300 topics with $\epsilon=10^{-12}$} + \label{fig:top10avg} +\end{figure*} + +\begin{figure} + \centering + \includegraphics[width=.50\textwidth,height=.35\textwidth]{plots/model_topic_probs.eps} + \caption{The inherent strength of each topic in descending order} + \label{fig:topicProbs} +\end{figure} +\end{comment} + +\begin{comment} +\subsection{Matching Topics} + +In the previous experiment, LDA and NMF regularly produced the most coherent +topics, thus. With such similar scores, we wish to know whether or not the two +models are learning similar topics. For example, are the best 10 topics from +LDA equivalent to the best 10 topics from NMF? To address this possibility, we +find the coherence between a pair of topics, $V$ and $Z$ with the following +measure: + +$$pairCoherence(V, Z) = \sum_{v_i \in V, z_j \in Z} score(v_i, z_i)$$ + +Now, we can compare the coherence, or relatedness, between topics +between two models by first comparing the $pairCoherence$ between all topic +combinations between two models and then finding the best matching topics with +the Hungarian Algorithm, which finds an optimal bipartite matching. If two +models are learning the same topics, we would expect the best matching to be +high, otherwise we can be confidence that the two models are learning unique +sets of topics, and thus users could potentially use both models. + +\begin{table}[h] +\footnotesize +\center +\begin{tabular}{|c|c|p{1.75in}|} +\hline +Quality & Model & Topic Terms \\ +\hline +\multirow{2}{*}{Best} +& LDA & wine wines bottle grapes made winery cabernet grape pinot red \\ +& NMF & tannins chardonnay sauvignon wine 2000 vintages tasting merlot cabernet wines \\ +\hline +\multirow{2}{*}{Worst} +& LDA & page front paper article news writer 24 16 28 read \\ +& NMF & lists designations 3 7 serials boy 2 witchcraft 8 paperbacks \\ +\hline +\end{tabular} +\label{tab:match-words} +\caption{The top 10 words from the best and worst matching topics from LDA and +NMF} +\end{table} + +We show the $pairCoherence$ scores first in Figure +\ref{fig:paired-weights} using both coherence scoring methods. This plots the +best, the average, and the median matching scores between LDA and NMF as we +learn a variable number of topics. The maximum scores show that both LDA and +NMF are learning at least one highly similar topic. Consider the best paired +topics from LDA and NMF when using the UCI measure in table +\ref{tab:match-words}. Here, both models clearly learned a topic about wines +and wine making. Also as expected, the two least connected topics have no +noticeable connection. Furthermore, the medians and averages indicate that the +rest of the topics are also mutually coherent. + +We last consider the relation between $pairCoherence$ and the topic coherence +for the topics from each model. Figure \ref{fig:score-weight-300} makes this +comparison directly for each model. Under both measures the $pairCoherence$ and +topic coherence show a clear but somewhat weak correlation, as the +$pairCoherence$ increases, so does the topic coherence, especially for the best +matched topics. + +\end{comment} +\subsection{Word Similarity Tasks} + +\begin{figure*}[h!t!b!] + \centering + \subfloat[UMass]{\includegraphics[width=.50\textwidth,height=.35\textwidth]{plots/umassNoSmoothing-ranks.eps}} + \subfloat[UCI]{\includegraphics[width=.50\textwidth,height=.35\textwidth]{plots/uciNoSmoothing-ranks.eps}} + \caption{Correlation between topic coherence and topic ranking in + classification} + \label{fig:topic-ranks} +\end{figure*} + +\begin{figure*}[h!t!b!] + \centering + \subfloat[UMass]{\includegraphics[width=.50\textwidth,height=.35\textwidth]{plots/umassNoSmoothing-rank-500.eps}} + \subfloat[UCI]{\includegraphics[width=.50\textwidth,height=.35\textwidth]{plots/uciNoSmoothing-rank-500.eps}} + \caption{Comparison between topic coherence and topic rank with 500 topics} + \label{fig:ranks500} +\end{figure*} + +The initial evaluations for each coherence measure asked human judges to +directly evaluate topics \cite{newman10uci,mimno11umass}. We expand upon this +comparison to human judgments by considering word similarity tasks that have +often been used to evaluate distributional semantic spaces +\cite{jurgens10sspace}. Here, we use the learned topics as generalized +semantics describing our knowledge about words. If a model's topics generalize +the knowledge accurately, we would expect similar words, such as ``cat'' and +``dog'', to be represented with a similar set of topics. Rather than evaluating +individual topics, this similarity task considers the knowledge within the +entire set of topics, the topics act as more compact representation for the +known words in a corpus. + +We use the \newcite{rubenstein65wordsim} and \newcite{finkelstein02relatedness} +word similarity tasks. In each task, human judges were asked to evaluate the +similarity or relatedness between different sets of word pairs. Fifty-One +Evaluators for the \newcite{rubenstein65wordsim} dataset were given 65 pairs of +words and asked to rate their similarity on a scale from 0 to 4, where a higher +score indicates a more similar word pair. \newcite{finkelstein02relatedness} +broadens the word similarity evaluation and asked 13 to 16 different subjects +to rate 353 word pairs on a scale from 0 to 10 based on their relatedness, where +relatedness includes similarity and other semantic relations. We can evaluate +each topic model by computing the cosine similarity between each pair of words +in the evaluate set and then compare the model's ratings to the human ratings by +ranked correlation. A high correlation signifies that the topics closely model +human judgments. + +Figure \ref{fig:wordsim} displays the results. SVD and LDA both surpass NMF on +the Rubenstein \& Goodenough test while SVD is clearly the best model on the +Finklestein et. al test. While our first experiment showed that SVD was the +worst model in terms of topic coherence scores, this experiment indicates that +SVD provides an accurate, stable, and reliable approximation to human judgements +of similarity and relatedness between word pairs in comparison to other topic +models. + +\subsection{Coherence versus Classification} + +For our final experiment, we examine the relationship between topic +coherence and classification accuracy for each topic model. We suspect that +highly coherent topics, and coherent topic models, will perform better for +classification. We address this question by performing a document +classification task using the topic representations of documents as input features +and examine the relationship between topic coherence and the usefulness of the +corresponding feature for classification. + +We trained each topic model with all 92,600 New York Times articles as before. +We use the section labels provided for each article as class labels, where each +label indicates the on-line section(s) under which the article was published and +should thus be related to the topics contained in each article. To reduce the +noise in our data set we narrow down the articles to those that have only one +label and whose label is applied to at least 2000 documents. This results in +57,696 articles with label distributions listed in Table \ref{tab:labels}. We +then represent each document using columns in the topic by document matrix $H$ +learned for each topic model. + +\begin{table}[htbp] + \centering + \begin{tabular}{lr|lr} + Label & Count & Label & Count \\ \hline + New York and Region & 11219 & U.S. & 3675 \\ + Paid Death Notices & 11152 & Arts & 3437 \\ + Opinion & 8038 & World & 3330 \\ + Business & 7494 & Style & 2137 \\ + Sports & 7214 + \end{tabular} + \caption{Section label counts for New York Times articles used for + classification} + \label{tab:labels} +\end{table} + +For each topic model trained on N topics, we performed stratified 10-fold +cross-validation on the 57,696 labeled articles. In each fold, +we build an automatically-sized bagged ensemble of unpruned CART-style decision +trees\cite{banfield07compareensemble} on 90\% of the +dataset\footnote{The precise choice of the classifier scheme matters +little, as long as it is accurate, speedy, and robust to label noise; +all of which is true of the choice here.}, use that ensemble +to assign labels to the other 10\%, and measure the accuracy of that assignment. +Figure \ref{fig:predict} shows the average classification accuracy over all ten +folds for each model. Interestingly, SVD has slightly, but statistically +significantly, higher accuracy results than both NMF and LDA. Furthermore, +performance quickly increases and plateaus with well under 50 topics. + +Our bagged decision trees can also determine the importance of each feature +during classification. We evaluate the strength of each topic during +classification by tracking the number of times each node in our decision trees +observe each topic, please see \cite{Caruana06miningcitizen} for more details. +Figure \ref{fig:ranks500} plot the relationship between this feature ranking and +the topic coherence for each topic when training LDA, SVD, and NMF on 500 +topics. Most topics for each model provide little classification information, +but SVD shows a much higher rank for several topics with a relatively higher +coherence score. Interestingly, for all models, the most coherent topics are +not the most informative. Figure \ref{fig:topic-ranks} plots a more compact +view of this same relationship: the Spearman rank correlation between +classification feature rank and topic coherence. NMF shows the highest +correlation between rank and coherence, but none of the models show a high +correlation when using more than 100 topics. SVD has the lowest +correlation, which is probably due to the model's overall low coherence yet high +classification accuracy. + diff --git a/papers/2012_emnlp_topic_coherence/figures/Faceted-search.png b/papers/2012_emnlp_topic_coherence/figures/Faceted-search.png new file mode 100644 index 00000000..033c7659 Binary files /dev/null and b/papers/2012_emnlp_topic_coherence/figures/Faceted-search.png differ diff --git a/papers/2012_emnlp_topic_coherence/figures/Smoothed_LDA.png b/papers/2012_emnlp_topic_coherence/figures/Smoothed_LDA.png new file mode 100644 index 00000000..e8b2fc6e Binary files /dev/null and b/papers/2012_emnlp_topic_coherence/figures/Smoothed_LDA.png differ diff --git a/papers/2012_emnlp_topic_coherence/figures/Wikipedia-logo.png b/papers/2012_emnlp_topic_coherence/figures/Wikipedia-logo.png new file mode 100644 index 00000000..56e06a93 Binary files /dev/null and b/papers/2012_emnlp_topic_coherence/figures/Wikipedia-logo.png differ diff --git a/papers/2012_emnlp_topic_coherence/figures/google-dog-search.png b/papers/2012_emnlp_topic_coherence/figures/google-dog-search.png new file mode 100644 index 00000000..885c9246 Binary files /dev/null and b/papers/2012_emnlp_topic_coherence/figures/google-dog-search.png differ diff --git a/papers/2012_emnlp_topic_coherence/figures/the_new_york_times_logo_8983D9A61EC52.jpg b/papers/2012_emnlp_topic_coherence/figures/the_new_york_times_logo_8983D9A61EC52.jpg new file mode 100644 index 00000000..ef04e342 Binary files /dev/null and b/papers/2012_emnlp_topic_coherence/figures/the_new_york_times_logo_8983D9A61EC52.jpg differ diff --git a/papers/2012_emnlp_topic_coherence/figures/topic-connection.pdf b/papers/2012_emnlp_topic_coherence/figures/topic-connection.pdf new file mode 100644 index 00000000..a1ee2cf5 Binary files /dev/null and b/papers/2012_emnlp_topic_coherence/figures/topic-connection.pdf differ diff --git a/papers/2012_emnlp_topic_coherence/introduction.tex b/papers/2012_emnlp_topic_coherence/introduction.tex new file mode 100644 index 00000000..aec4f7f7 --- /dev/null +++ b/papers/2012_emnlp_topic_coherence/introduction.tex @@ -0,0 +1,53 @@ +\label{sec:introduction} +Topic models learn bags of related words from large corpora without any +supervision. Based on the words used within a document, they mine topic level +relations by assuming that a single document covers a small set of concise +topics. Once learned, these topics often correlate well with human concepts. +For example, one model might produce topics that cover ideas such as government +affairs, sports, and movies. With these unsupervised methods, we can extract +useful semantic information in a variety of tasks that depend on identifying +unique topics or concepts, such as distributional semantics +\cite{jurgens10sspace}, word sense induction +\cite{vandeCruys11latentWsi,brody09ldawsi}, and information retrieval +\cite{andrzejewski11ldaIR}. + +When using a topic model, we are primarily concerned with the degree to which +the learned topics match human judgments and help us differentiate between +ideas. But until recently, the evaluation of these models has been ad hoc and +application specific. Evaluations have ranged from fully automated intrinsic +evaluations to manually crafted extrinsic evaluations. Previous extrinsic +evaluations have used the learned topics to compactly represent a small fixed +vocabulary and compared this distributional space to human judgments of +similarity \cite{jurgens10sspace}. But these evaluations are hand constructed +and often costly to perform for domain-specific topics. Conversely, intrinsic +measures have evaluated the amount of information encoded by the topics, where +perplexity is one common example\cite{wallach2009evaluation}, however, \newcite{gerrish09tealeaves} +found that these intrinsic measures do not always correlate with semantically +interpretable topics. Furthermore, few evaluations have used the same metrics +to compare distinct approaches such as Latent Dirichlet Allocation (LDA) +\cite{blei03lda}, Latent Semantic Analysis (LSA) \cite{landauer97solution}, and +Non-negative Matrix Factorization (NMF) \cite{Lee00algorithmsfor}. This has +made it difficult to know which method is most useful for a given application, +or in terms of extracting useful topics. + +We now provide a comprehensive and automated evaluation of these three distinct +models (LDA, LSA, NMF), for automatically learning semantic topics. While these +models have seen significant improvements, they still represent the core +differences between each approach to modeling topics. For our evaluation, we +use two recent automated coherence measures \cite{mimno11umass,newman10uci} +originally designed for LDA that bridge the gap between comparisons to +human judgments and intrinsic measures such as perplexity. We consider several +key questions: +\begin{enumerate*} +{\footnotesize + \item How many topics should be learned? + \item How many learned topics are useful? + \item How do these topics relate to often used semantic tests? + \item How well do these topics identify similar documents? + } +\end{enumerate*} + +We begin by summarizing the three topic models and highlighting their key +differences. We then describe the two metrics. Afterwards, we focus on a +series of experiments that address our four key questions and finally conclude +with some overall remarks. diff --git a/papers/2012_emnlp_topic_coherence/mallet-classifier-accuracy-topics.pdf b/papers/2012_emnlp_topic_coherence/mallet-classifier-accuracy-topics.pdf new file mode 100644 index 00000000..f0da4277 Binary files /dev/null and b/papers/2012_emnlp_topic_coherence/mallet-classifier-accuracy-topics.pdf differ diff --git a/papers/2012_emnlp_topic_coherence/plots/10mean-uciNoSmoothing.eps b/papers/2012_emnlp_topic_coherence/plots/10mean-uciNoSmoothing.eps new file mode 100644 index 00000000..d9fd76eb --- /dev/null +++ b/papers/2012_emnlp_topic_coherence/plots/10mean-uciNoSmoothing.eps @@ -0,0 +1,2288 @@ +%!PS-Adobe-3.0 EPSF-3.0 +%%DocumentNeededResources: font Helvetica +%%+ font Helvetica-Bold +%%+ font Helvetica-Oblique +%%+ font Helvetica-BoldOblique +%%+ font Symbol +%%Title: R Graphics Output +%%Creator: R Software +%%Pages: (atend) +%%BoundingBox: 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cl +489.60 23.02 489.60 23.02 cl +0.00 0.00 504.00 504.00 cl +0.00 0.00 504.00 504.00 cl +0.00 0.00 504.00 504.00 cl +ep +%%Trailer +%%Pages: 1 +%%EOF diff --git a/papers/2012_emnlp_topic_coherence/presentation.tex b/papers/2012_emnlp_topic_coherence/presentation.tex new file mode 100644 index 00000000..51482370 --- /dev/null +++ b/papers/2012_emnlp_topic_coherence/presentation.tex @@ -0,0 +1,553 @@ +\documentclass[compress]{beamer} +\usepackage{multirow} +\newcommand{\argmin}{\operatornamewithlimits{argmin}} +\def\qeq{\mathrel{% + \mathchoice{\QEQ}{\QEQ}{\scriptsize\QEQ}{\tiny\QEQ}% +}} +\def\QEQ{{% + \setbox0\hbox{$\sim$}% + \rlap{\hbox to \wd0{\hss!\hss}}\box0 +}} + +\usetheme{Warsaw} +\setbeamertemplate{navigation symbols}{} +\useoutertheme[footline=authortitle,subsection=false]{miniframes} +\title[Exploring Topic Coherence over many models and many topics] + {Exploring Topic Coherence over many models and many topics} + +\author[Stevens, Kegelmeyer, Andrzejewski, Buttler] + {Keith Stevens \inst{1} \inst{2} \and + Philip Kegelmeyer \inst{3} \and \\ + David Andrzejewski \inst{1} \and + David Buttler \inst{1}} +\institute{\inst{1} Lawrence Livermore National Lab \and + \inst{2} University of California, Los Angeles \and + \inst{3} Sandia National Lab +\thanks{ + \tiny +This work was performed under the auspices of the U.S. Department of Energy by +Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 +(LLNL-XXXX-XXXXXX) and by Sandia National Laboratory under Contract +DE-AC04-94AL85000.} + } + +\date{} + +\begin{document} + +\frame{ + \titlepage +} + +\section{Motivation} + +\begin{frame}{Why Learn Topic Models?} + +\begin{columns} +\begin{column}[1]{5cm} +Suppose you're given a lot of articles to read: +\includegraphics[width=.50\textwidth,height=.30\textwidth]{figures/the_new_york_times_logo_8983D9A61EC52.jpg} +\includegraphics[width=.40\textwidth,height=.30\textwidth]{figures/Wikipedia-logo.png} +\end{column} +\begin{column}[2]{5cm} +Questions: +\begin{itemize} +\item How do you grok the corpus? +\item How do you discover relevant events? +\item How do you make these tasks easy? +\end{itemize} +\end{column} +\end{columns} + +\pause +\begin{block}{Bjarne Stroustrup} +A high level of abstraction is good +\end{block} + +\pause +\begin{itemize} +\item Abstraction reduces the complexity of a dataset +\item Topic models learn good abstractions +\end{itemize} +\end{frame} + +\begin{frame}{Testing the value of learned abstractions} +\begin{block}{Intuition: Topics correspond to concepts, sort of} +\begin{enumerate} +\item Topics represent distinctions matching human intuition +\item Uncovered Topics reduce complexity when comparing words and documents +\end{enumerate} +\end{block} + +\begin{overlayarea}{\textwidth}{4cm} +\only<2>{ + All three models are used interchangeably: + \begin{itemize} + \item Word Similarity Judgements (Reisinger \& Mooney 11, Jurgens+ 10) + \item Document Classification (Mimno+ 09, Foltz \& Dumais 92) + \item Information Retrieval (Andrzejewski \& Buttler 11, Hoffman 99, etc) + \end{itemize} + $ \rightarrow $ Time to compare all three again \\ +} +\only<3>{ +\pause +Big Question: Why/When Should We Use Particular Models? +\begin{enumerate} +\item How do you evaluate an entire model? +\item Is one model strictly better than other? +\item Does each model specialize for a task? +\end{enumerate} +} +\only<4->{ +\pause +Three Evaluations testing our intuitions and questions: +\begin{enumerate} +\item Compactly evaluate quality of both topics and entire models +\item Compare abstracted word representations to topic coherence +\item Compare abstracted document representations to topic coherence +\end{enumerate} +\pause +Core Question: does semantic quality of a topic model indicate that the model +has good abstract representations? +} +\end{overlayarea} +\end{frame} + +\begin{frame}{Outline} +\begin{enumerate} +\item Motivation for modeling semantics +\item Topic Models + \begin{enumerate} + \item A shared framework + \item Latent Dirichlet Allocation + \item Decompositional approaches + \end{enumerate} +\item Topic Coherence Metrics + \begin{enumerate} + \item Purpose + \item Two measures of coherence + \end{enumerate} +\item Comparing three evaluations + \begin{enumerate} + \item Evaluating complete models + \item Evaluating semantic judgements + \item Evaluating document categories + \end{enumerate} +\item Conclusions +\end{enumerate} +\end{frame} + +\section{Topic Models} + +\subsection{A shared framework} + +\begin{frame}{The Big Topic Modeling Picture} +\center +\includegraphics[width=.80\textwidth,height=.40\textwidth]{figures/topic-connection.pdf} + +Topic Models learn latent factors that +\begin{enumerate} +\item Link together related Words +\item Link together related Documents +\item Link words to documents +\item Represent a semantic "concept" +\end{enumerate} +\end{frame} + +\begin{frame}{A basic framework for Topic Models} +\begin{block}{Input} +A large collection of English documents such as New York Times articles +\end{block} + +\begin{block}{Output} +Two Matrices: +\begin{itemize} +\item W records the strength between words and topics +\item H records the strength between documents and topics +\end{itemize} +Together, W and H should abstractly summarize the semantic content of the input +\end{block} +\end{frame} + +\subsection{Latent Dirichlet Allocation} + +\begin{frame}{A generative story for topics} +\begin{block}{Latent Dirichlet Allocation} +To "write" a document +\begin{enumerate} +\item Choose a mixture of topics for the document +\item For each word to write + \begin{enumerate} + \item Pick a topic from your mixture + \item Write down a word from the topic + \end{enumerate} +\end{enumerate} +\end{block} + +\begin{columns} +\begin{column}[1]{6cm} +\begin{itemize} +\item $\theta$ represents how each document generates topics ($H$) +\item $\varphi$ represents how each topic generates words ($W'$) +\end{itemize} +\end{column} +\begin{column}[2]{4cm} +\includegraphics[width=.80\textwidth,height=.40\textwidth]{figures/Smoothed_LDA.png} +\end{column} +\end{columns} +\end{frame} + +\subsection{A decompositional approach} + +\begin{frame}{A story of decomposition for topics} +\begin{block}{Latent Semantic Analysis} +\begin{enumerate} +\item Form a Term X Document matrix (A) +\item Weight the counts to enhance informative words +\item Split the matrix along multiple, \textit{interesting} dimensions +\end{enumerate} +\end{block} + +\begin{overlayarea}{\textwidth}{4cm} +\only<1>{ +\begin{columns} +\begin{column}[1]{4cm} +The decomposition results in two matrices +\begin{itemize} +\item W: A Word by Topic matrix +\item H: A Document by Topic matrix +\end{itemize} +\end{column} +\begin{column}[2]{6cm} +The Source of generalization: +\begin{itemize} +\item Latent, interesting dimensions smooth the data +\item Smoothing flattens out noisy features +\end{itemize} +\end{column} +\end{columns} +} +\only<2>{ +\pause +\begin{columns} +\begin{column}[1]{5.5cm} +Singular Value Decomposition: +\begin{itemize} +\item Decompose: $ A = U \Sigma V' $ +\item Select top $k$ dimensions +\item Minimize Frobenius norm: +$ || A - U_k \Sigma_k V_k' ||^2 $ +\item $ W = U_k \Sigma_k $, $ H = (\Sigma_k V_k')' $ +\end{itemize} +\end{column} +\begin{column}[2]{5cm} +Features/Issues: +\begin{itemize} +\item Arbitrary latent dimensions +\item Possibly negative relationships +\item No Succinct interpretation +\end{itemize} +\end{column} +\end{columns} +} +\only<3>{ +\pause +\begin{columns} +\begin{column}[1]{5.5cm} +Nonnegative Matrix Factorization: +\begin{itemize} +\item Decompose: $ A = W H' $ +\item Minimize Frobenius norm: +$ || A - W H' ||^2 $ +\item Enforce non-negative values +\end{itemize} +\end{column} +\begin{column}[2]{5cm} +Features/Issues: +\begin{itemize} +\item Decomposition forms probabilities +\item Easy to interpret +\item Approximated Solution +\end{itemize} +\end{column} +\end{columns} +} +\end{overlayarea} +\end{frame} + +\section{Topic Coherence Metrics} + +\subsection{Purpose} + +\begin{frame}{The idea behind coherence metrics} +\begin{block}{Reminder: Topics correspond to concepts} +\begin{enumerate} +\item Topics represent distinctions matching human intuition +\item Uncovered Topics reduce complexity when comparing words and documents +\end{enumerate} +\end{block} +\begin{overlayarea}{\textwidth}{4cm} +\only<1>{ + Realization: \\ + $ correlation(perlexity, human\_intuition) \sim 0 $ +} +\only<2>{ +Evaluation Intuition: Words forming topics should be \textit{related}. +\[ +Coherence(topic) = \sum_{w_1,w_2 \in topic} sim(w_1, w_2) +\] + +$sim(w_i, w_j)$ returns the strength of \textit{relatedness} between two words. +} +\end{overlayarea} +\end{frame} + +\subsection{Two measures of coherence} + +\begin{frame}{Computing relatedness: An Intrinsic approach} +\begin{block}{UMass Topic Coherence} +\[ +sim(w_i, w_j) = log \frac{ D(w_i, w_j) + \epsilon } { D(w_j) } +\] +\end{block} +High Level Idea: +\begin{itemize} +\item Measure frequency of words occurring the \textbf{same} document +\item Hi co-occurrence in relation to unigram occurrence = related +\end{itemize} + +Key Detail: Compute counts on the training corpus. +\end{frame} + +\begin{frame}{Computing relatedness: An Extrinsic approach} +\begin{block}{UCI Topic Coherence} +\[ +sim(w_i, w_j) = log \frac{ p(w_i, w_j) + \epsilon } { p(w_i) p(w_j) } +\] +\end{block} + +High Level Idea: +\begin{itemize} +\item Compute Pointwise Mutual Information between words +\item High PMI = related +\end{itemize} + +Key Detail: Compute counts on representative, external corpus. \\ +We used a 20 word sliding window on Wikipedia for our counts. +\end{frame} + +\section{Comparing three evaluations} + +\begin{frame}{Some sample learned topics} +\begin{table}[h!t!b!] +\center +\tiny +\begin{tabular}{|cll|} +\multicolumn{1}{c}{Model} & Label & \multicolumn{1}{l}{Top Words} \\ +\hline +\multicolumn{3}{l}{\textbf{High Quality Topics}} \\ +\hline +\multirow{2}{*}{LDA} +% 500-32 +& interview & told asked wanted interview people made thought time called knew +\\ +% 500-176 +& wine & wine wines bottle grapes made winery cabernet grape pinot red +\\ +\hline +\multirow{2}{*}{NMF} +% 500-144 +& grilling & grilled sweet spicy fried pork dish shrimp menu dishes sauce +\\ +% 500-120 +& cloning & embryonic cloned embryo human research stem embryos cell cloning cells +\\ +\hline +\multirow{2}{*}{SVD} +% 500-5 +& cooking & sauce food restaurant water oil salt chicken pepper wine cup +\\ +% 500-25 +& stocks & fund funds investors weapons stocks mutual stock movie film show +\\ +\hline + +\multicolumn{3}{l}{\textbf{Low Quality Topics}} \\ +\hline +\multirow{2}{*}{LDA} +% 500-290 +& rates & 10-yr rate 3-month percent 6-month bds bd 30-yr funds robot +\\ +% 500-340 +& charity & fund contributions .com family apartment charities rent 22d children assistance +\\ +\hline +\multirow{2}{*}{NMF} +% 500-76 +& plants & stem fruitful stems trunk fruiting currants branches fence currant espalier +\\ +% 500-33 +& farming & buzzards groundhog prune hoof pruned pruning vines wheelbarrow tree clematis +\\ +\hline +\multirow{2}{*}{SVD} +% 500-7 +& city & building city area buildings p.m. floors house listed eat-in a.m. +\\ +% 500-160 +& time & p.m. system study a.m. office political found school night yesterday +\\ +\hline +\end{tabular} +\caption{Top 10 words from several high and low quality topics learned +automatically from 92,000 New York Times articles.} +\end{table} +\end{frame} + +\begin{frame}{Experimental Setup} +\begin{block}{New York Times 2003 dataset} +\begin{itemize} +\item $\sim$ 92,000 articles, each with multiple section labels +\item Discard stop words, infrequent words ($< 200$ occurrences) +\item No Stemming +\end{itemize} +\end{block} + +Three Topic Models: LDA, LSA using SVD, LSA using NMF \\ +Many numbers of topics: 1-100, 100-500 in steps of 10. + +\end{frame} + +\subsection{Evaluating Complete Models} + +\begin{frame}{Topic Coherence Measures} +\only<1>{ +\begin{block}{Multiple ways of evaluating a complete model} +\begin{itemize} +\item Average Coherence +\item Best Coherence +\item Entropy of Coherence scores +\end{itemize} +\end{block} +} +\only<5>{ + \center + Average UMass Topic Coherence with $\epsilon=10^{-12}$ +\includegraphics[width=\textwidth,height=.55\textwidth]{plots/mean-umassNoSmoothing.pdf} +} +\only<4>{ + \center + Average UMass Topic Coherence with $\epsilon=10^{0}$ +\includegraphics[width=\textwidth,height=.55\textwidth]{plots/mean-umass.pdf} +} +\only<3>{ + \center + Average UCI Topic Coherence with $\epsilon=10^{-12}$ +\includegraphics[width=\textwidth,height=.55\textwidth]{plots/mean-uciNoSmoothing.pdf} +} +\only<2>{ + \center + Average UCI Topic Coherence with $\epsilon=10^{0}$ +\includegraphics[width=\textwidth,height=.55\textwidth]{plots/mean-uci.pdf} +} +\end{frame} + +\subsection{Evaluating semantic judgements} + +\begin{frame}{Evaluating the latent word representations} + +\only<1>{ +\begin{block}{Humans are good at judging relatedness} +Example: $cat \sim dog$, $cat \qeq umbrella$ \\ +Goal: Word representations should approximate human judgements +\end{block} + +\begin{columns} +\begin{column}[1]{5cm} +\begin{tabular}{lll} +Word & Word & Relatedness \\ +\hline +coast & forest & 0.85 \\ +monk & oracle & 0.91 \\ +fruit & furnace & 0.05 \\ +cord & smile & 0.02 \\ +\hline +\end{tabular} +\end{column} +\begin{column}[2]{5cm} +\begin{enumerate} +\item Compute cosine similarity between latent word representations +\item Compute correlation between similarity measures and human judgements +\end{enumerate} +\end{column} +\end{columns} +} +\only<2>{ +\center +Correlation with Rubenstein \& Goodenough word pairs +\includegraphics[width=\textwidth,height=.55\textwidth]{plots/rng_wordsim.pdf} +} +\only<3>{ +\center +Correlation with WordSim-353 word pairs +\includegraphics[width=\textwidth,height=.55\textwidth]{plots/353_wordsim.pdf} +} +\end{frame} + +\subsection{Evaluating document categories} + +\begin{frame}{Evaluating the latent document representations} + +\only<1>{ +\begin{block}{Categories on documents set a semantic scope} +Example: World News articles are related to each other, less so to Science +articles \\ +Goal: Document representations should encode these differences +\end{block} + +Setup: +\begin{itemize} +\item Train and Test a classifier using stratified 10-fold cross validation +\item Train with Bagged Ensembles of CART-decision trees +\item Compare proposed labels to known categories +\item Higher accuracy means better representation +\end{itemize} +} +\only<2>{ + \center + Classification accuracy of latent document representations +\includegraphics[width=\textwidth,height=.55\textwidth]{plots/avatar_classifier.pdf} +} +\only<3>{ + \center + Correlation between feature ranking and UCI Topic Coherence + \includegraphics[width=\textwidth,height=.55\textwidth]{plots/uciNoSmoothing-ranks.pdf} +} +\only<4>{ + \center + Classification Accuracy with more classifiers + \includegraphics[width=\textwidth,height=.55\textwidth]{mallet-classifier-accuracy-topics.pdf} +} +\end{frame} + +\section{Conclusions} + +\begin{frame}{Topic Model Conclusions} +\begin{itemize} +\item Key Finding: Each model is tuned for a different task +\item SVD is better for finding compact, abstract representations +\item LDA is better for learning meaningful/understandable topics +\item NMF does moderately well on all tasks but never shines +\end{itemize} + +\begin{block}{Take away point} +Pick your model based on your task and test for it carefully. +\end{block} + +\pause + Lastly, Code to run experiments is provided on GitHub: + https://github.com/fozziethebeat/TopicModelComparison \footnote{But the New + York Times dataset isn't, see the LDC for that} +\end{frame} + +\end{document} diff --git a/papers/2012_emnlp_topic_coherence/topic-models.tex b/papers/2012_emnlp_topic_coherence/topic-models.tex new file mode 100644 index 00000000..f4141cb0 --- /dev/null +++ b/papers/2012_emnlp_topic_coherence/topic-models.tex @@ -0,0 +1,187 @@ +\label{sec:topic-models} + +We evaluate three latent factor models that have seen widespread usage: +\begin{enumerate*} +{\small + \item Latent Dirichlet Allocation + \item Latent Semantic Analysis with Singular Value Decomposition + \item Latent Semantic Analysis with Non-negative Matrix Factorization +} +\end{enumerate*} + +Each of these models were designed with different goals and are supported +by different statistical theories. We consider both LSA models as topic models +as they have been used in a variety of similar contexts such as distributional +similarity \cite{jurgens10sspace} and word sense induction +\cite{vandeCruys11latentWsi,brody09ldawsi}. We evaluate these distinct models +on two shared tasks (1) grouping together similar words while separating +unrelated words and (2) distinguishing between documents focusing on different +concepts. + +We distill the different models into a shared representation consisting of two +sets of learned relations: how words interact with topics and how topics +interact with documents. For a corpus with $\mathcal{D}$ documents and +$\mathcal{V}$ words, we denote these relations in terms of $\mathcal{T}$ topics +as +\begin{description} +\item[(1)] a $\mathcal{V} \times \mathcal{T}$ matrix, $W$, that indicates the strength +each word has in each topic, and +\item[(2)] a $\mathcal{T} \times \mathcal{D}$ matrix, $H$, that indicates the strength each topic +has in each document. + +\end{description} +$\mathcal{T}$ serves as a common parameter to each model. + +\subsection{Latent Dirichlet Allocation} + +Latent Dirichlet Allocation \cite{blei03lda} learns the relationships +between words, topics, and documents by assuming documents are generated by a +particular probabilistic model. It first assumes that there are a fixed set of +topics, $\mathcal{T}$ used throughout the corpus, and each topic $z$ is associated with a +multinomial distribution over the vocabulary $\Phi_{z}$, which is drawn from a +Dirichlet prior $Dir(\beta)$. A given document $D_i$ is then generated by the +following process +\begin{enumerate} +{\small +\item Choose $\Theta_i \sim Dir(\alpha)$, a topic distribution for $D_i$ +\item For each word $w_j \in D_i$: + \begin{enumerate} + \item Select a topic $z_j \sim \Theta_i$ + \item Select the word $w_j \sim \Phi_{z_j}$ + \end{enumerate} +} +\end{enumerate} + +In this model, the $\Theta$ distributions represent the probability of each +topic appearing in each document and the $\Phi$ distributions represent the +probability of words being used for each topic. These two sets of distributions +correspond to our $H$ and $W$ matrices, respectively. The process above defines +a generative model; given the observed corpus, we use collapsed Gibbs sampling +implementation found in Mallet\footnote{http://mallet.cs.umass.edu/} to infer +the values of the latent variables $\Phi$ and $\Theta$ +\cite{griffiths_steyvers04}. The model relies only on two additional hyper +parameters, $\alpha$ and $\beta$, that guide the distributions. + +\begin{table*}[h!t!b!] +\footnotesize +\center +\begin{tabular}{|cllcc|} +\multicolumn{1}{c}{Model} & Label & Top Words & UMass & \multicolumn{1}{l}{UCI} \\ +\hline +\multicolumn{3}{l}{\textbf{High Quality Topics}} \\ +\hline +\multirow{2}{*}{LDA} +% 500-32 +& interview & told asked wanted interview people made thought time called knew +& -2.52 & 1.29 \\ +% 500-176 +& wine & wine wines bottle grapes made winery cabernet grape pinot red +& -1.97 & 1.30 \\ +\hline +\multirow{2}{*}{NMF} +% 500-144 +& grilling & grilled sweet spicy fried pork dish shrimp menu dishes sauce +& -1.01 & 1.98 \\ +% 500-120 +& cloning & embryonic cloned embryo human research stem embryos cell cloning cells +& -1.84 & 1.46 \\ +\hline +\multirow{2}{*}{SVD} +% 500-5 +& cooking & sauce food restaurant water oil salt chicken pepper wine cup +& -1.87 & -1.21 \\ +% 500-25 +& stocks & fund funds investors weapons stocks mutual stock movie film show +& -2.30 & -1.88 \\ +\hline + +\multicolumn{3}{l}{\textbf{Low Quality Topics}} \\ +\hline +\multirow{2}{*}{LDA} +% 500-290 +& rates & 10-yr rate 3-month percent 6-month bds bd 30-yr funds robot +& -1.94 & -12.32 \\ +% 500-340 +& charity & fund contributions .com family apartment charities rent 22d children assistance +& -2.43 & -8.88 \\ +\hline +\multirow{2}{*}{NMF} +% 500-76 +& plants & stem fruitful stems trunk fruiting currants branches fence currant espalier +& -3.12 & -12.59 \\ +% 500-33 +& farming & buzzards groundhog prune hoof pruned pruning vines wheelbarrow tree clematis +& -1.90 & -12.56 \\ +\hline +\multirow{2}{*}{SVD} +% 500-7 +& city & building city area buildings p.m. floors house listed eat-in a.m. +& -2.70 & -8.03 \\ +% 500-160 +& time & p.m. system study a.m. office political found school night yesterday +& -1.67 & -7.02 \\ +\hline +\end{tabular} +\caption{Top 10 words from several high and low quality topics when ordered by +the UCI Coherence Measure. Topic labels were chosen in an ad hoc manner only to +briefly summarize the topic's focus.} +\label{tab:best} +\end{table*} + + +\subsection{Latent Semantic Analysis} + +Latent Semantic Analysis \cite{landauer97solution,landauer98lsa} learns topics +by first forming a traditional term by document matrix used in information +retrieval and then smoothing the counts to enhance the weight of informative +words. Based on the original LSA model, we use the Log-Entropy transform. +LSA then decomposes this smoothed, term by document matrix in order to +generalize observed relations between words and documents. For both LSA models, +we used implementations found in the S-Space +package.\footnote{https://github.com/fozziethebeat/S-Space} + +Traditionally, LSA has used the Singular Value Decomposition, but we also +consider Non-negative Matrix Factorization as we've seen NMF applied in similar +situations \cite{pauca04nmfIR} and others have found a connection between NMF +and Probabilistic Latent Semantic Analysis \cite{ding08nmfPlsa}, an extension to +LSA. We later refer to these two LSA models simply as SVD and NMF to emphasize +the difference in factorization method. + +\paragraph{Singular Value Decomposition} +decomposes $M$ into three smaller matrices +$$ +M=U \Sigma V^{T} +$$ +\noindent +and minimizes Frobenius norm of $M$'s reconstruction error with the constraint +that the rows of $U$ and $V$ are orthonormal eigenvectors. Interestingly, the +decomposition is agnostic to the number of desired dimensions. Instead, the +rows and columns in $U$ and $V^T$ are ordered based on their descriptive power, +i.e. how well they remove noise, which is encoded by the diagonal singular value +matrix $\Sigma$. As such, reduction is done by retaining the first +$\mathcal{T}$ rows and columns from $U$ and $V^T$. For our generalization, we +use $W=U \Sigma$ and $H = \Sigma V^T$. We note that values in $U$ and $V^T$ can +be both negative and positive, preventing a straightforward interpretation as +unnormalized probabilities + +\paragraph{Non-negative Matrix Factorization} +also factorizes $M$ by minimizing the reconstruction error, but with only one +constraint: the decomposed matrices consist of only non-negative values. +In this respect, we can consider it to be +learning an unnormalized probability distributions over topics. We use the original +Euclidean least squares definition of NMF\footnote{We note that the +alternative KL-Divergence form of NMF has been directly linked to PLSA +\cite{ding08nmfPlsa}}. Formally, NMF is defined as + +$$M = W H$$ +\noindent +where $H$ and $W$ map directly onto our generalization. As in the original NMF +work, we learn these unnormalized probabilities by initializing each set of +probabilities at random and update them according to the following iterative +update rules + +$$ +\begin{array}{cc} + W = W \frac{M H^T}{W H H^T} & H = H \frac{W^T M}{W^T W H} \\ +\end{array} +$$ diff --git a/papers/2012_emnlp_topic_coherence/topic_coherence.bib b/papers/2012_emnlp_topic_coherence/topic_coherence.bib new file mode 100644 index 00000000..0e63cbbd --- /dev/null +++ b/papers/2012_emnlp_topic_coherence/topic_coherence.bib @@ -0,0 +1,301 @@ +@inproceedings{wallach2009evaluation, + author={Hanna Wallach and Iain Murray and Ruslan Salakhutdinov and David Mimno}, + title={Evaluation Methods for Topic Models}, + booktitle={Proceedings of the 26th International Conference on Machine Learning (ICML)}, + publisher={Omnipress}, + year={2009} +} + +@article{baroni09wacky, + author = {Marco Baroni and Silvia Bernardini and Adriano Ferraresi and Eros Zanchetta}, + year = 2009, + title = {The {W}a{C}ky Wide Web: A Collection of Very Large Linguistically Processed Web-Crawled Corpora}, + journal = {Language Resources and Evaluation}, + volume = 43, + number = 3, + pages = {209-226}, +} + +@inproceedings{chang2009tealeaves, +author = {Jonathan Chang and Jordan Boyd-Graber and Chong Wang and Sean Gerrish and David M. 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Both metrics have been shown to align with human evaluations and +provide a balance between internal measures of information gain and comparisons +to human ratings of coherent topics. We improve upon the measures by +introducing new aggregate measures that allows for comparing complete topic +models. We further compare the automated measures to other metrics for topic +models, comparison to manually crafted semantic tests and document +classification. Our experiments reveal that LDA and LSA each have different +strengths; LDA best learns descriptive topics while LSA is best at creating a +compact semantic representation of documents and words in a corpus. +\end{abstract} + +\section{Introduction} +\input{introduction} + + +\section{Topic Models} +\input{topic-models} + +\section{Coherence Measures} +\input{coherence-metrics} + +\section{Evaluation} +\input{evaluation} + +\section{Discussion and Conclusion} +\input{discussion} + +\section{Acknowledgments} + +This work was performed under the auspices of the U.S. Department of Energy by +Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 +(LLNL-CONF-522871) and by Sandia National Laboratory under Contract +DE-AC04-94AL85000. + +\bibliographystyle{acl2012} +\bibliography{topic_coherence} + +\end{document}