callback({ "items" : [ { "publisher" : "Morgan Kaufmann", "booktitle" : "Proceedings of Speech and Natural Language Workshop", "pub-type" : "inproceedings", "uri" : "urn:723d84005f6d3259597ee5c3698234ce", "pages" : "312??????318", "date" : "1991", "author" : "Lewis, D. D.", "year" : "1991", "type" : "Publication", "label" : "Evaluating text categorization", "key" : "lewis_evaluating_1991" }, { "publisher" : "{MIT} Press", "pub-type" : "book", "uri" : "urn:a48e3b28b41a967dc7e5da509aa82b6e", "pages" : "1207--1245", "date" : "2000", "author" : [ "Scholkopf, B.", "Smola, A. J.", "Williamson, R. C.", "Bartlett, P. L." ], "volume" : "12", "type" : "Publication", "year" : "2000", "label" : "New Support Vector Algorithms", "key" : "scholkopf_new_2000" }, { "publisher" : "Association for Computational Linguistics", "url" : "http://portal.acm.org/citation.cfm?id=1220575.1220618", "booktitle" : "Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing", "pub-type" : "inproceedings", "uri" : "urn:bc83228f176dcb29c6135a821f32a06d", "pages" : "339--346", "date" : "2005", "author" : [ "Popescu, {Ana-Maria}", "Etzioni, Oren" ], "keywords" : [ "information extraction", "opinion mining", "product features", "sentiment analysis" ], "type" : "Publication", "year" : "2005", "abstract" : "Consumers are often forced to wade through many on-line reviews in order to make an informed product choice. This paper introduces Opine, an unsupervised information-extraction system which mines reviews in order to build a model of important product features, their evaluation by reviewers, and their relative quality across {products.Compared} to previous work, Opine achieves 22\\% higher precision (with only 3\\% lower recall) on the feature extraction task. Opine\'s novel use of relaxation labeling for finding the semantic orientation of words in context leads to strong performance on the tasks of finding opinion phrases and their polarity.", "label" : "Extracting product features and opinions from reviews", "address" : "Vancouver, British Columbia, Canada", "key" : "popescu_extracting_2005" }, { "journal" : "Artificial Intelligence", "pub-type" : "article", "uri" : "urn:eff3c6af220579a4366d48341a831dd9", "pages" : "91--134", "date" : "2005", "number" : "1", "author" : [ "Etzioni, Oren", "Cafarella, Michael", "Downey, Doug", "Popescu, {Ana-Maria}", "Shaked, Tal", "Soderland, Stephen", "Weld, Daniel S.", "Yates, Alexander" ], "keywords" : [ "machine learning", "ner", "unsupervised", "web" ], "volume" : "165", "type" : "Publication", "year" : "2005", "label" : "Unsupervised named-entity extraction from the Web: An experimental study", "key" : "etzioni_unsupervised_2005" }, { "publisher" : "{ACM}", "url" : "http://portal.acm.org/citation.cfm?id=1040890", "booktitle" : "Proceedings of the 10th international conference on Intelligent user interfaces", "pub-type" : "inproceedings", "uri" : "urn:23291daf7e442e0634e02d4ea323d6c4", "pages" : "260--262", "date" : "2005", "author" : [ "{Al-Mubaid}, Hisham", "Chen, Ping" ], "keywords" : [ "information retrieval", "similarity detection", "synonymy" ], "doi" : "10.1145/1040830.1040890", "type" : "Publication", "year" : "2005", "abstract" : "This paper presents a new context-based method for automatic detection and extraction of similar and related words from texts. Finding similar words is a very important task for many {NLP} applications including anaphora resolution, document retrieval, text segmentation, and text summarization. Here we use word similarity to improve search quality for search engines in (general and) specific domains. Our method is based on rules for extracting the words in the neighborhood of a target word, then connecting this with the surroundings of other occurrences of the same word in the (training) text corpus. This is an on-going work, and is still under extensive testing. The preliminary results, however, are promising and encouraging more work in this direction.", "isbn" : "1-58113-894-6", "label" : "Context-based similar words detection and its application in specialized search engines", "address" : "San Diego, California, {USA}", "key" : "al-mubaid_context-based_2005" }, { "booktitle" : "Proceedings of the sixth international conference on Language Resources and Evaluation {(LREC} 2008)", "pub-type" : "inproceedings", "uri" : "urn:a59986154733bb7291bd1c032905db9e", "date" : "2008", "author" : [ "Widdows, D.", "Ferraro, K." ], "keywords" : [ "open source", "semantics", "wordspace" ], "type" : "Publication", "year" : "2008", "label" : "Semantic Vectors: A Scalable Open Source Package and Online Technology Management Application", "key" : "widdows_semantic_2008" }, { "publisher" : "Lawrence Erlbaum Associates Ltd", "booktitle" : "International Joint Conference on Artificial Intelligence", "pub-type" : "inproceedings", "uri" : "urn:b8e928c3936b48e99be3c76665472fb5", "pages" : "1136", "date" : "2005", "author" : "Turney, P. D.", "keywords" : [ "latent relational analysis", "machine learning", "semantic similarity", "semantics" ], "volume" : "19", "type" : "Publication", "year" : "2005", "label" : "Measuring Semantic Similarity by Latent Relational Analysis", "key" : "turney_measuring_2005" }, { "url" : "http://arxiv.org/abs/cs/0608100", "journal" : "cs/0608100", "pub-type" : "article", "uri" : "urn:d036bd0f92bc8ffc9a57573858acbfdc", "date" : "2006-08", "author" : "Turney, Peter D", "keywords" : [ "semantic similarity", "semantics" ], "month" : "August", "type" : "Publication", "year" : "2006", "note" : "Computational Linguistics, (2006), 32(3), 379-416", "abstract" : "There are at least two kinds of similarity. Relational similarity is correspondence between relations, in contrast with attributional similarity, which is correspondence between attributes. When two words have a high degree of attributional similarity, we call them synonyms. When two pairs of words have a high degree of relational similarity, we say that their relations are analogous. For example, the word pair mason:stone is analogous to the pair carpenter:wood. This paper introduces Latent Relational Analysis {(LRA),} a method for measuring relational similarity. {LRA} has potential applications in many areas, including information extraction, word sense disambiguation, and information retrieval. Recently the Vector Space Model {(VSM)} of information retrieval has been adapted to measuring relational similarity, achieving a score of 47\\% on a collection of 374 college-level multiple-choice word analogy questions. In the {VSM} approach, the relation between a pair of words is characterized by a vector of frequencies of predefined patterns in a large corpus. {LRA} extends the {VSM} approach in three ways: (1) the patterns are derived automatically from the corpus, (2) the Singular Value Decomposition {(SVD)} is used to smooth the frequency data, and (3) automatically generated synonyms are used to explore variations of the word pairs. {LRA} achieves 56\\% on the 374 analogy questions, statistically equivalent to the average human score of 57\\%. On the related problem of classifying semantic relations, {LRA} achieves similar gains over the {VSM.}", "label" : "Similarity of Semantic Relations", "key" : "turney_similarity_2006" }, { "journal" : "{PSYCHOLOGICAL} {REVIEW-NEW} {YORK-}", "pub-type" : "article", "uri" : "urn:3d46353f10d74ecbef780a90a91b1fd8", "pages" : "211--240", "date" : "1997", "author" : [ "Landauer, T. K.", "Dumais, S. T." ], "volume" : "104", "keywords" : [ "clustering", "latent semantic analysis", "linear algebra", "machine learning" ], "type" : "Publication", "year" : "1997", "label" : "A Solution to Plato\'s Problem: The Latent Semantic Analysis Theory of Acquisition, Induction, and Representation of Knowledge", "key" : "landauer_solution_1997" }, { "url" : "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.34.9579", "journal" : "{SIAM} Review", "pub-type" : "article", "uri" : "urn:4c29e3ff8a62cde588a62a577aded8f8", "pages" : "573---595", "date" : "1995", "author" : [ "Berry, M. W", "Dumais, S. T", "O\'brien, G. W", "Berry, Michael W", "Dumais, Susan T", "Gavin" ], "volume" : "37", "doi" : "10.1.1.34.9579", "type" : "Publication", "year" : "1995", "label" : "Using linear algebra for intelligent information retrieval", "key" : "berry_using_1995" }, { "booktitle" : "Proceedings of the International Conference on Semantic Systems {(I-Semantics??????} 08), Graz. Forthcoming", "pub-type" : "inproceedings", "uri" : "urn:cd990aeeb4ec9822ee9060dbd343440c", "date" : "2008", "author" : [ "Chamberlain, J.", "Poesio, M.", "Kruschwitz, U." ], "keywords" : [ "anaphora resolution", "games", "human computation", "phrases" ], "type" : "Publication", "year" : "2008", "label" : "Phrase Detectives: A Web-based Collaborative Annotation Game", "key" : "chamberlain_phrase_2008" }, { "url" : "http://arxiv.org/abs/0801.4307", "journal" : "Proceedings of the 5th International Conference on Recent Advances in Soft Computing {(RASC} 2004), Nottingham, {UK}", "pub-type" : "article", "uri" : "urn:b9f6178964652481f46d22be5936b7ef", "date" : "2004", "author" : [ "Aickelin, Uwe", "Chen, Qi" ], "keywords" : [ "Computer Science - Artificial {Intelligence", "Computer} Science - Computers and {Society", "Computer} Science - Neural and Evolutionary Computing" ], "type" : "Publication", "year" : "2004", "abstract" : "We combine Artificial Immune Systems {\'AIS\',} technology with Collaborative Filtering {\'CF\'} and use it to build a movie recommendation system. We already know that Artificial Immune Systems work well as movie recommenders from previous work by Cayzer and Aickelin 3, 4, 5. Here our aim is to investigate the effect of different affinity measure algorithms for the {AIS.} Two different affinity measures, Kendalls Tau and Weighted Kappa, are used to calculate the correlation coefficients for the movie recommender. We compare the results with those published previously and show that Weighted Kappa is more suitable than others for movie problems. We also show that {AIS} are generally robust movie recommenders and that, as long as a suitable affinity measure is chosen, results are good.", "label" : "On Affinity Measures for Artificial Immune System Movie Recommenders", "key" : "aickelin_affinity_2004" }, { "journal" : "Proc. of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics", "pub-type" : "article", "uri" : "urn:bd529c8be1c28aec65d23c8e7edbd3ed", "pages" : "505????512", "date" : "2006", "author" : "Hockenmaier, J.", "year" : "2006", "type" : "Publication", "label" : "Creating a {CCGbank} and a wide-coverage {CCG} lexicon for German", "key" : "hockenmaier_creatingccgbank_2006" }, { "journal" : "American Anthropologist", "pub-type" : "article", "uri" : "urn:6ff020e8bfc9d1d7caa693d688e54b41", "pages" : "65--79", "date" : "1984", "number" : "1", "author" : [ "Kay, P.", "Kempton, W." ], "keywords" : [ "linguistics", "sapir-whorf" ], "volume" : "86", "type" : "Publication", "year" : "1984", "label" : "What Is the {Sapir-Whorf} Hypothesis?", "key" : "kay_what_1984" }, { "journal" : "Proceedings of {ACL} Workshop on Intrinsic and Extrinsic Evaluation Measures for Machine Translation and/or Summarization", "pub-type" : "article", "uri" : "urn:603279284242386645d67630d595462e", "date" : "2005", "author" : [ "Liu, D.", "Gildea, D." ], "keywords" : [ "machine translation", "mt eval", "syntax" ], "year" : "2005", "type" : "Publication", "label" : "Syntactic Features for Evaluation of Machine Translation", "key" : "liu_syntactic_2005" }, { "booktitle" : "{AAAI} \'04", "pub-type" : "inproceedings", "uri" : "urn:a8b8e864581f275c32987011e2b2d5e1", "pages" : "755--760", "date" : "2004", "author" : [ "Hu, M.", "Liu, B." ], "keywords" : [ "opinion mining", "sentiment analysis" ], "type" : "Publication", "year" : "2004", "label" : "Mining Opinion Features in Customer Reviews", "key" : "hu_mining_2004" }, { "publisher" : "{ACM}", "url" : "http://portal.acm.org/citation.cfm?id=1183614.1183625", "pub-type" : "inproceedings", "uri" : "urn:347cbb6ff2b382ebf5219856e19b5da6", "pages" : "43--50", "date" : "2006", "author" : [ "Zhuang, Li", "Jing, Feng", "Zhu, {Xiao-Yan}" ], "keywords" : [ "review mining", "summarization" ], "doi" : "10.1145/1183614.1183625", "type" : "Publication", "year" : "2006", "abstract" : "With the flourish of the Web, online review is becoming a more and more useful and important information resource for people. As a result, automatic review mining and summarization has become a hot research topic recently. Different from traditional text summarization, review mining and summarization aims at extracting the features on which the reviewers express their opinions and determining whether the opinions are positive or negative. In this paper, we focus on a specific domain - movie review. A multi-knowledge based approach is proposed, which integrates {WordNet,} statistical analysis and movie knowledge. The experimental results show the effectiveness of the proposed approach in movie review mining and summarization.", "isbn" : "1-59593-433-2", "label" : "Movie review mining and summarization", "address" : "Arlington, Virginia, {USA}", "key" : "zhuang_movie_2006" }, { "journal" : "Proceedings of the 6th Conference of the Association for Machine Translation in the Americas", "pub-type" : "article", "uri" : "urn:98aa87ddc13071b3baa45af2104a3b8f", "date" : "2004", "author" : [ "Lavie, A.", "Sagae, K.", "Jayaraman, S." ], "keywords" : [ "machine translation", "mt eval", "recall" ], "year" : "2004", "type" : "Publication", "label" : "The Significance of Recall in Automatic Metrics for {MT} Evaluation", "key" : "lavie_significance_2004" }, { "journal" : "Proceedings of the 11th Conference on Theoretical and Methodological Issues in Machine Translation {(TMI)}", "pub-type" : "article", "uri" : "urn:9c3077d69bad98a3e0518c0c69bdb6aa", "date" : "2007", "author" : [ "Mehay, D.", "Brew, C." ], "keywords" : [ "dependency grammar", "machine translation", "mt eval", "syntax" ], "year" : "2007", "type" : "Publication", "label" : "{BLEUATRE:} Flattening Syntactic Dependencies for {MT} Evaluation", "key" : "mehay_bleuatre:_2007" }, { "journal" : "Proceedings of the 4th International Conference on Language Resources and Evaluation {(LREC} 2004", "pub-type" : "article", "uri" : "urn:f3285f9196c2e230b4bb26d8bd7e55a0", "pages" : "1115??????1118", "date" : "2004", "author" : [ "Kamps, J.", "Marx, M.", "Mokken, R. J.", "Rijke, M. de" ], "volume" : "4", "type" : "Publication", "year" : "2004", "label" : "Using {WordNet} to measure semantic orientation of adjectives", "key" : "kamps_using_2004" }, { "booktitle" : "Proceedings of the Tenth {ACM} {SIGKDD} International Conference on Knowledge Discovery and Data Mining", "pub-type" : "inproceedings", "uri" : "urn:90b7a45a67fcaeed012c2b03deabd6a2", "date" : "2004", "author" : [ "Hu, M.", "Liu, B." ], "keywords" : [ "opinion mining", "sentiment analysis" ], "type" : "Publication", "year" : "2004", "label" : "Mining and Summarizing Customer Reviews", "key" : "hu_mining_2004-1" }, { "journal" : "Proceedings of the 5th {LREC}", "pub-type" : "article", "uri" : "urn:9d23617b1af499aa730a577b1d0c2542", "date" : "2006", "author" : [ "Gimenez, J.", "Amigo, E." ], "keywords" : [ "machine translation", "mt eval" ], "year" : "2006", "type" : "Publication", "label" : "{IQMT:} A Framework for Automatic Machine Translation Evaluation", "key" : "gimenez_iqmt:framework_2006" }, { "journal" : "Proceedings of the {COLING/ACL} on Main conference poster sessions", "pub-type" : "article", "uri" : "urn:d966746d45001a24e2e53e88b0c32d54", "pages" : "17--24", "date" : "2006", "author" : [ "Amig????, E.", "Gim????nez, J.", "Gonzalo, J.", "M????rquez, L." ], "keywords" : [ "machine translation", "mt eval" ], "type" : "Publication", "year" : "2006", "label" : "{MT} evaluation: human-like vs. human acceptable", "key" : "amig_mt_2006" }, { "label" : "Labelled Dependencies in Machine Translation Evaluation", "key" : "owczarzak_labelled_2007", "type" : "Publication", "pub-type" : "article", "uri" : "urn:3fee6fcea97c4f7573cc9e9b8c5cef24", "journal" : "Proceedings of the Second Workshop on Statistical Machine Translation" }, { "publisher" : "Association for Computational Linguistics", "url" : "http://portal.acm.org/citation.cfm?id=1073083.1073135", "pub-type" : "inproceedings", "uri" : "urn:c3701da25c00694e464d9e76f15b1df6", "pages" : "311--318", "date" : "2001", "author" : [ "Papineni, Kishore", "Roukos, Salim", "Ward, Todd", "Zhu, {Wei-Jing}" ], "keywords" : [ "bleu", "machine translation", "mt eval" ], "type" : "Publication", "year" : "2001", "abstract" : "Human evaluations of machine translation are extensive but expensive. Human evaluations can take months to finish and involve human labor that can not be reused. We propose a method of automatic machine translation evaluation that is quick, inexpensive, and language-independent, that correlates highly with human evaluation, and that has little marginal cost per run. We present this method as an automated understudy to skilled human judges which substitutes for them when there is need for quick or frequent evaluations.", "label" : "{BLEU:} a method for automatic evaluation of machine translation", "address" : "Philadelphia, Pennsylvania", "key" : "papineni_bleu:method_2001" }, { "url" : "http://dx.doi.org/10.1007/11430919_37", "booktitle" : "Advances in Knowledge Discovery and Data Mining", "pub-type" : "inbook", "uri" : "urn:ab2005186d1364b1eb603f8b7fb51428", "pages" : "301--311", "date" : "2005", "author" : [ "Matsumoto, Shotaro", "Takamura, Hiroya", "Okumura, Manabu" ], "keywords" : [ "machine learning", "opinion mining", "sentiment classification", "svms" ], "type" : "Publication", "year" : "2005", "abstract" : "Document sentiment classification is a task to classify a document according to the positive or negative polarity of its opinion (favorable or unfavorable). We propose using syntactic relations between words in sentences for document sentiment classification. Specifically, we use text mining techniques to extract frequent word sub-sequences and dependency sub-trees from sentences in a document dataset and use them as features of support vector machines. In experiments on movie review datasets, our classifiers obtained the best results yet published using these data.", "label" : "Sentiment Classification Using Word Sub-sequences and Dependency Sub-trees", "key" : "matsumoto_sentiment_2005" }, { "journal" : "Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics {(ACL-2007)}", "pub-type" : "article", "uri" : "urn:2ed48e9803fc796a163c5a3c36d310c0", "date" : "2007", "author" : [ "Albrecht, J. S.", "Hwa, R." ], "keywords" : [ "machine learning", "machine translation", "mt", "svms" ], "year" : "2007", "type" : "Publication", "label" : "A Re-examination of Machine Learning Approaches for {Sentence-Level} {MT} Evaluation", "key" : "albrecht_re-examination_2007" }, { "publisher" : "{ACM}", "url" : "http://portal.acm.org/citation.cfm?id=775152.775226&type=series", "booktitle" : "Proceedings of the 12th international conference on World Wide Web", "pub-type" : "inproceedings", "uri" : "urn:425fe6732fd3d8d75178ae92d21d09a0", "pages" : "519--528", "date" : "2003", "author" : [ "Dave, Kushal", "Lawrence, Steve", "Pennock, David M." ], "keywords" : [ "opinion mining", "sentiment analysis" ], "doi" : "10.1145/775152.775226", "type" : "Publication", "year" : "2003", "abstract" : "The web contains a wealth of product reviews, but sifting through them is a daunting task. Ideally, an opinion mining tool would process a set of search results for a given item, generating a list of product attributes (quality, features, etc.) and aggregating opinions about each of them (poor, mixed, good). We begin by identifying the unique properties of this problem and develop a method for automatically distinguishing between positive and negative reviews. Our classifier draws on information retrieval techniques for feature extraction and scoring, and the results for various metrics and heuristics vary depending on the testing situation. The best methods work as well as or better than traditional machine learning. When operating on individual sentences collected from web searches, performance is limited due to noise and ambiguity. But in the context of a complete web-based tool and aided by a simple method for grouping sentences into attributes, the results are qualitatively quite useful.", "isbn" : "1-58113-680-3", "label" : "Mining the peanut gallery: opinion extraction and semantic classification of product reviews", "address" : "Budapest, Hungary", "key" : "dave_miningpeanut_2003" }, { "journal" : "Proceedings of the {ACL}", "pub-type" : "article", "uri" : "urn:ae2a442550059a00fcdbe1930b95a4e1", "pages" : "271??????278", "date" : "2004", "author" : [ "Pang, B.", "Lee, L." ], "keywords" : [ "opinion mining", "sentiment analysis" ], "type" : "Publication", "year" : "2004", "label" : "A sentimental education: Sentiment analysis using subjectivity summarization based on minimum cuts", "key" : "pang_sentimental_2004" }, { "publisher" : "{ACM}", "url" : "http://portal.acm.org/citation.cfm?id=383972", "booktitle" : "Proceedings of the 24th annual international {ACM} {SIGIR} conference on Research and development in information retrieval", "pub-type" : "inproceedings", "uri" : "urn:80bd9a842676d2bf7d9004f43818987c", "pages" : "120--127", "date" : "2001", "author" : [ "Lavrenko, Victor", "Croft, W. Bruce" ], "keywords" : [ "information retrieval", "language models", "relevance" ], "doi" : "10.1145/383952.383972", "type" : "Publication", "year" : "2001", "abstract" : "We explore the relation between classical probabilistic models of information retrieval and the emerging language modeling approaches. It has long been recognized that the primary obstacle to effective performance of classical models is the need to estimate arelevance model: probabilities of words in the relevant class. We propose a novel technique for estimating these probabilities using the query alone. We demonstrate that our technique can produce highly accurate relevance models, addressing important notions of synonymy and polysemy. Our experiments show relevance models outperforming baseline language modeling systems on {TREC} retrieval and {TDT} tracking tasks. The main contribution of this work is an effective formal method for estimating a relevance model with no training data.", "isbn" : "1-58113-331-6", "label" : "Relevance based language models", "address" : "New Orleans, Louisiana, United States", "key" : "lavrenko_relevance_2001" }, { "publisher" : "{ACM}", "url" : "http://portal.acm.org/citation.cfm?id=1352793.1352842", "booktitle" : "Proceedings of the 2nd international conference on Ubiquitous information management and communication", "pub-type" : "inproceedings", "uri" : "urn:55b63086492d4ec06f4e7928a6f1c3b3", "pages" : "230--235", "date" : "2008", "author" : [ "Lee, Dongjoo", "Jeong, {Ok-Ran}", "Lee, Sang-goo" ], "keywords" : [ "opinion mining", "opinion summarization", "sentiment analysis" ], "doi" : "10.1145/1352793.1352842", "type" : "Publication", "year" : "2008", "abstract" : "As people leave on the Web their opinions on products and services they have used, it has become important to develop methods of (semi-)automatically classifying and gauging them. The task of analyzing such data, collectively called customer feedback data, is known as opinion mining. Opinion mining consists of several steps, and multiple techniques have been proposed for each step. In this paper, we survey and analyze various techniques that have been developed for the key tasks of opinion mining. On the basis of our survey and analysis of the techniques, we provide an overall picture of what is involved in developing a software system for opinion mining.", "isbn" : "978-1-59593-993-7", "label" : "Opinion mining of customer feedback data on the web", "address" : "Suwon, Korea", "key" : "lee_opinion_2008" }, { "journal" : "Proceedings of the Workshop on Statistical Machine Translation", "pub-type" : "article", "uri" : "urn:d2ba3f1ec34bcaccebb336ca62be2c66", "pages" : "102????121", "date" : "2006", "author" : [ "Koehn, P.", "Monz, C." ], "keywords" : [ "machine translation", "mt eval" ], "type" : "Publication", "year" : "2006", "label" : "Manual and automatic evaluation of machine translation between european languages", "key" : "koehn_manual_2006" }, { "journal" : "Knowledge Discovery and Data Mining", "pub-type" : "article", "uri" : "urn:542c492d931c644960ffcb0be8ca2dc9", "pages" : "80--86", "date" : "1998", "author" : [ "Liu, B.", "Hsu, W.", "Ma, Y." ], "keywords" : [ "association rules", "machine learning" ], "type" : "Publication", "year" : "1998", "label" : "Integrating Classification and Association Rule Mining", "key" : "liu_integrating_1998" }, { "label" : "Heterogeneous Automatic {MT} Evaluation Through {Non-Parametric} Metric Combinations", "key" : "combinations_heterogeneous_????", "keywords" : [ "machine translation", "mt eval" ], "type" : "Publication", "pub-type" : "article", "author" : "Combinations, {TNPM}", "uri" : "urn:4a658507f2459c9f3385d61e157d6291" }, { "journal" : "Proceedings of Workshop on Statistical Machine Translation {(WMT)} at the 45th Annual Meeting of the Association of Computational Linguistics {(ACL-07)}", "pub-type" : "article", "uri" : "urn:11268cb89c9d331eafb5306499487f28", "date" : "2007", "author" : [ "Lavie, A.", "Agarwal, A." ], "keywords" : [ "machine translation", "meteor", "mt eval" ], "year" : "2007", "type" : "Publication", "label" : "Meteor: An Automatic Metric for {MT} Evaluation with High Levels of Correlation with Human Judgments", "key" : "lavie_meteor:automatic_2007" }, { "booktitle" : "Symposium on Affective Language in Human and Machine", "pub-type" : "inproceedings", "uri" : "urn:d96356215d53f77ea61597d7c8b75c60", "date" : "2008", "author" : [ "Fahrni, A.", "Klenner, M." ], "keywords" : [ "opinion mining", "sentiment analysis" ], "year" : "2008", "type" : "Publication", "label" : "Old Wine or Warm Beer: {Target-Specific} Sentiment Analysis of Adjectives", "address" : "University of Aberdeen, Aberdeen, Scotland", "key" : "fahrni_old_2008" }, { "label" : "Scalable Collaborative Filtering with Jointly Derived Neighborhood Interpolation Weights", "key" : "bell_scalable_????", "type" : "Publication", "pub-type" : "article", "author" : [ "Bell, R. M.", "Koren, Y." ], "uri" : "urn:f1fe294c781a638116225d14bf770054" }, { "journal" : "Proceedings of {SSST,} {NAACL-HLT/AMTA} Workshop on Syntax and Structure in Statistical Translation", "pub-type" : "article", "uri" : "urn:df1955b8e08eb1f778a0120c17caf658", "date" : "2007", "author" : [ "Owczarzak, K.", "Genabith, J. van", "Way, A." ], "keywords" : [ "dependency grammar", "machine translation", "mt eval" ], "year" : "2007", "type" : "Publication", "label" : "{Dependency-Based} Automatic Evaluation for Machine Translation", "key" : "owczarzak_dependency-based_2007" }, { "publisher" : "Association for Computational Linguistics", "url" : "http://portal.acm.org/citation.cfm?id=1118692&dl=GUIDE,", "pub-type" : "inproceedings", "uri" : "urn:8d50d1f83b0d469fa48dcf8ca36014ec", "pages" : "116--122", "date" : "2002", "author" : [ "Chklovski, Timothy", "Mihalcea, Rada" ], "keywords" : [ "human computation", "wsd" ], "type" : "Publication", "year" : "2002", "abstract" : "Open Mind Word Expert is an implemented active learning system for collecting word sense tagging from the general public over the Web. It is available at http://teach-computers.org. We expect the system to yield a large volume of high-quality training data at a much lower cost than the traditional method of hiring lexicographers. We thus propose a Senseval-3 lexical sample activity where the training data is collected via Open Mind Word Expert. If successful, the collection process can be extended to create the definitive corpus of word sense information.", "label" : "Building a sense tagged corpus with open mind word expert", "key" : "chklovski_buildingsense_2002" }, { "publisher" : "Association for Computational Linguistics", "url" : "http://portal.acm.org/citation.cfm?id=1118704&dl=GUIDE,", "pub-type" : "inproceedings", "uri" : "urn:57bcb7116c0a4a6307aa263c22477226", "pages" : "79--86", "date" : "2002", "author" : [ "Pang, Bo", "Lee, Lillian", "Vaithyanathan, Shivakumar" ], "type" : "Publication", "year" : "2002", "abstract" : "We consider the problem of classifying documents not by topic, but by overall sentiment, e.g., determining whether a review is positive or negative. Using movie reviews as data, we find that standard machine learning techniques definitively outperform human-produced baselines. However, the three machine learning methods we employed {(Naive} Bayes, maximum entropy classification, and support vector machines) do not perform as well on sentiment classification as on traditional topic-based categorization. We conclude by examining factors that make the sentiment classification problem more challenging.", "label" : "Thumbs up?: sentiment classification using machine learning techniques", "key" : "pang_thumbs_2002" }, { "booktitle" : "Proceedings of {LREC}", "pub-type" : "inproceedings", "uri" : "urn:5f9927b956f0adb64ec81d373a3bb6be", "pages" : "417--422", "date" : "2006", "author" : [ "Esuli, A.", "Sebastiani, F." ], "keywords" : [ "opinion mining", "sentiment analysis", "wordnet" ], "type" : "Publication", "year" : "2006", "label" : "{SentiWordNet:} A publicly available lexical resource for opinion mining", "key" : "esuli_sentiwordnet:publicly_2006" }, { "label" : "Human Evaluation of Machine Translation Through Binary System Comparisons", "key" : "vilar_human_2007", "type" : "Publication", "pub-type" : "article", "uri" : "urn:3cab75b6b4b313830ca95f6aa5c87c96", "journal" : "Proceedings of the Second Workshop on Statistical Machine Translation" }, { "label" : "Computational Aspects of Prediction Markets", "key" : "pennock_computational_????", "type" : "Publication", "pub-type" : "article", "author" : [ "Pennock, D. M.", "Sami, R." ], "uri" : "urn:d4817035f096f970baeec0598f732669" }, { "journal" : "Proceedings of the 39th Annual Meeting on Association for Computational Linguistics", "pub-type" : "article", "uri" : "urn:6bc0bd8b63de5d15d6b94d6dfce86a38", "pages" : "148--155", "date" : "2001", "author" : [ "{Corston-Oliver}, S.", "Gamon, M.", "Brockett, C." ], "keywords" : [ "machine learning", "machine translation", "mt eval" ], "type" : "Publication", "year" : "2001", "label" : "A machine learning approach to the automatic evaluation of machine translation", "key" : "corston-oliver_machine_2001" }, { "journal" : "Proceedings of the 10th International Conference on Theoretical and Methodological Issues in Machine Translation", "pub-type" : "article", "uri" : "urn:b9e72ca5dad65ae0af6a3157251b4aff", "date" : "2004", "author" : [ "Kulesza, A.", "Shieber, S. M." ], "keywords" : [ "machine learning", "machine translation", "mt eval", "svms" ], "year" : "2004", "type" : "Publication", "label" : "A learning approach to improving sentence-level {MT} evaluation", "key" : "kulesza_learning_2004" }, { "journal" : "Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics", "pub-type" : "article", "uri" : "urn:41b37146b6ed5d73bbad5095b1a413b3", "pages" : "455--462", "date" : "2006", "author" : [ "Kauchak, D.", "Barzilay, R." ], "keywords" : [ "machine translation", "mt eval", "paraphrases" ], "type" : "Publication", "year" : "2006", "label" : "Paraphrasing for automatic evaluation", "key" : "kauchak_paraphrasing_2006" }, { "pub-type" : "techreport", "institution" : "Technical Report {LAMPTR-125/CS-TR-4754/UMIACS-TR-2005-57,} University of Maryland, College Park, {MD}", "uri" : "urn:bc2cb716d7ddcf829f23189a65ad1991", "date" : "2005", "author" : [ "{Russo-Lassner}, G.", "Lin, J.", "Resnik, P." ], "keywords" : [ "machine translation", "mt eval", "paraphrases" ], "type" : "Publication", "year" : "2005", "label" : "A Paraphrase-based Approach to Machine Translation Evaluation", "key" : "russo-lassner_paraphrase-based_2005" }, { "publisher" : "Cambridge University Press", "pub-type" : "book", "uri" : "urn:ea851604a754ee5ca2073ed1ec90f3d7", "date" : "2008", "author" : [ "Manning, C. D.", "Raghavan, P.", "Sch????tze, H." ], "keywords" : "information retrieval", "type" : "Publication", "year" : "2008", "label" : "Introduction to Information Retrieval", "key" : "manning_introduction_2008" }, { "url" : "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.60.8645", "journal" : "In Proceedings of the 11th Conference of the European Chapter of the Association for Computational Linguistics {(EACL??????06}", "pub-type" : "article", "uri" : "urn:4eb27fd457e6619ca445751361b9e7d3", "date" : "2006", "author" : [ "Esuli, Andrea", "Sebastiani, Fabrizio" ], "keywords" : [ "opinion mining", "sentiment analysis" ], "doi" : "10.1.1.60.8645", "type" : "Publication", "year" : "2006", "label" : "Determining term subjectivity and term orientation for opinion mining", "key" : "esuli_determining_2006" }, { "publisher" : "{ACM}", "url" : "http://portal.acm.org/citation.cfm?id=1273496.1273596", "pub-type" : "inproceedings", "uri" : "urn:884d701b71130afb0bb678aa8702cd7c", "pages" : "791--798", "date" : "2007", "author" : [ "Salakhutdinov, Ruslan", "Mnih, Andriy", "Hinton, Geoffrey" ], "doi" : "10.1145/1273496.1273596", "type" : "Publication", "year" : "2007", "abstract" : "Most of the existing approaches to collaborative filtering cannot handle very large data sets. In this paper we show how a class of two-layer undirected graphical models, called Restricted Boltzmann Machines {(RBM\'s),} can be used to model tabular data, such as user\'s ratings of movies. We present efficient learning and inference procedures for this class of models and demonstrate that {RBM\'s} can be successfully applied to the Netflix data set, containing over 100 million user/movie ratings. We also show that {RBM\'s} slightly outperform carefully-tuned {SVD} models. When the predictions of multiple {RBM} models and multiple {SVD} models are linearly combined, we achieve an error rate that is well over 6\\% better than the score of Netflix\'s own system.", "isbn" : "978-1-59593-793-3", "label" : "Restricted Boltzmann machines for collaborative filtering", "address" : "Corvalis, Oregon", "key" : "salakhutdinov_restricted_2007" }, { "journal" : "The 2005 International Workshop on Spoken Language Translation", "pub-type" : "article", "uri" : "urn:aa65e49512fe39378a18e71307b7af72", "date" : "2005", "author" : [ "Hewavitharana, S.", "Zhao, B.", "Hildebrand, A. S.", "Eck, M.", "Hori, C.", "Vogel, S.", "Waibel, A." ], "type" : "Publication", "year" : "2005", "label" : "The {CMU} statistical machine translation system for {IWSLT2005}", "key" : "hewavitharana_cmu_2005" }, { "journal" : "Proceedings of the eighth {ACM} {SIGKDD} international conference on Knowledge discovery and data mining", "pub-type" : "article", "uri" : "urn:7820c8181b55adcafc282403e54b4db6", "pages" : "133--142", "date" : "2002", "author" : "Joachims, T.", "keywords" : [ "clickthrough", "machine learning", "search engines", "svms" ], "type" : "Publication", "year" : "2002", "label" : "Optimizing search engines using clickthrough data", "key" : "joachims_optimizing_2002" }, { "journal" : "Proceedings of {ACL}", "pub-type" : "article", "uri" : "urn:3822e7a525ad8a80a6086ba9b5386a1f", "date" : "2007", "author" : [ "Albrecht, J.", "Hwa, R." ], "keywords" : [ "machine learning", "machine translation", "mt eval", "svms" ], "year" : "2007", "type" : "Publication", "label" : "Regression for {Sentence-Level} {MT} Evaluation with Pseudo References", "key" : "albrecht_regression_2007" }, { "journal" : "Advances in Neural Information Processing Systems", "pub-type" : "article", "uri" : "urn:45edc0eacaa1f0dbc06e312462637cd8", "pages" : "625????632", "date" : "2002", "author" : [ "Collins, M.", "Duffy, N." ], "volume" : "14", "keywords" : [ "kernels", "machine learning", "nlp", "svms" ], "type" : "Publication", "year" : "2002", "label" : "Convolution kernels for natural language", "key" : "collins_convolution_2002" }, { "journal" : "Proc. 20th Int. Conf. Very Large Data Bases, {VLDB}", "pub-type" : "article", "uri" : "urn:eed345f43a3297fd3fc43de69379cdc1", "pages" : "487499", "date" : "1994", "author" : [ "Agrawal, R.", "Srikant, R." ], "volume" : "1215", "type" : "Publication", "year" : "1994", "label" : "Fast algorithms for mining association rules", "key" : "agrawal_fast_1994" }, { "url" : "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.3.901", "journal" : "In Proceedings of {ICML}", "pub-type" : "article", "uri" : "urn:df640ec98535dd5ff9ff5cd96b71f48e", "pages" : "704---711", "date" : "2003", "author" : [ "Si, Luo", "Jin, Rong" ], "keywords" : [ "collaborative {filtering", "EM} algorithm", "hmm", "machine learning", "recommender systems" ], "doi" : "10.1.1.3.901", "type" : "Publication", "year" : "2003", "label" : "Flexible mixture model for collaborative filtering", "key" : "si_flexible_2003" }, { "booktitle" : "Proceedings of {EMNLP}", "pub-type" : "inproceedings", "uri" : "urn:cb324cf2979b8e32a3bd2aa8a28cb89d", "pages" : "412????418", "date" : "2004", "author" : [ "Mullen, T.", "Collier, N." ], "keywords" : [ "machine learning", "opinion mining", "sentiment analysis", "svms" ], "type" : "Publication", "year" : "2004", "label" : "Sentiment analysis using support vector machines with diverse information sources", "key" : "mullen_sentiment_2004" }, { "journal" : "Proceedings of {COLING}", "pub-type" : "article", "uri" : "urn:718589c96646b42c4de3ebe2d49df14e", "pages" : "501??????507", "date" : "2004", "author" : [ "Lin, C. Y.", "Och, F. J." ], "keywords" : [ "machine translation", "mt eval" ], "type" : "Publication", "year" : "2004", "label" : "{ORANGE:} a Method for Evaluating Automatic Evaluation Metrics for Machine Translation", "key" : "lin_orange:method_2004" }, { "booktitle" : "Proceedings of the {GWA} {2006??????Global} {WordNet} Association Conference", "pub-type" : "inproceedings", "uri" : "urn:44cfa88efd3c19f7eb9ec3685962495c", "date" : "2006", "author" : "Mendes, S.", "type" : "Publication", "year" : "2006", "label" : "Adjectives in {WordNet}", "key" : "mendes_adjectives_2006" }, { "publisher" : "{ACM}", "url" : "http://portal.acm.org/citation.cfm?id=1341531.1341561", "pub-type" : "inproceedings", "uri" : "urn:d2481e5b1d1a0efaf7daef1ee5729231", "pages" : "231--240", "date" : "2008", "author" : [ "Ding, Xiaowen", "Liu, Bing", "Yu, Philip S." ], "keywords" : "context dependent opinions", "doi" : "10.1145/1341531.1341561", "type" : "Publication", "year" : "2008", "abstract" : "One of the important types of information on the Web is the opinions expressed in the user generated content, e.g., customer reviews of products, forum posts, and blogs. In this paper, we focus on customer reviews of products. In particular, we study the problem of determining the semantic orientations (positive, negative or neutral) of opinions expressed on product features in reviews. This problem has many applications, e.g., opinion mining, summarization and search. Most existing techniques utilize a list of opinion (bearing) words (also called opinion lexicon) for the purpose. Opinion words are words that express desirable (e.g., great, amazing, etc.) or undesirable (e.g., bad, poor, etc) states. These approaches, however, all have some major shortcomings. In this paper, we propose a holistic lexicon-based approach to solving the problem by exploiting external evidences and linguistic conventions of natural language expressions. This approach allows the system to handle opinion words that are context dependent, which cause major difficulties for existing algorithms. It also deals with many special words, phrases and language constructs which have impacts on opinions based on their linguistic patterns. It also has an effective function for aggregating multiple conflicting opinion words in a sentence. A system, called Opinion Observer, based on the proposed technique has been implemented. Experimental results using a benchmark product review data set and some additional reviews show that the proposed technique is highly effective. It outperforms existing methods significantly", "isbn" : "978-1-59593-927-9", "label" : "A holistic lexicon-based approach to opinion mining", "address" : "Palo Alto, California, {USA}", "key" : "ding_holistic_2008" }, { "journal" : "Intrinsic and Extrinsic Evaluation Measures for Machine Translation and/or Summarization", "pub-type" : "article", "uri" : "urn:a611e059eb0755a35919f5dd15c140dc", "date" : "2005", "author" : [ "Banerjee, S.", "Lavie, A." ], "keywords" : [ "machine translation", "meteor", "mt eval" ], "year" : "2005", "type" : "Publication", "label" : "{METEOR:} An Automatic Metric for {MT} Evaluation with Improved Correlation with Human Judgments", "key" : "banerjee_meteor:automatic_2005" }, { "publisher" : "Association for Computational Linguistics", "url" : "http://portal.acm.org/citation.cfm?id=1118693.1118699", "booktitle" : "Proceedings of the {ACL-02} conference on Empirical methods in natural language processing - Volume 10", "pub-type" : "inproceedings", "uri" : "urn:02279db49da3b3d9b4876f5a225cc56d", "pages" : "41--48", "date" : "2002", "author" : [ "Lee, Yoong Keok", "Ng, Hwee Tou" ], "type" : "Publication", "year" : "2002", "abstract" : "In this paper, we evaluate a variety of knowledge sources and supervised learning algorithms for word sense disambiguation on {SENSEVAL-2} and {SENSEVAL-1} data. Our knowledge sources include the part-of-speech of neighboring words, single words in the surrounding context, local collocations, and syntactic relations. The learning algorithms evaluated include Support Vector Machines {(SVM),} Naive Bayes, {AdaBoost,} and decision tree algorithms. We present empirical results showing the relative contribution of the component knowledge sources and the different learning algorithms. In particular, using all of these knowledge sources and {SVM} (i.e., a single learning algorithm) achieves accuracy higher than the best official scores on both {SENSEVAL-2} and {SENSEVAL-1} test data.", "label" : "An empirical evaluation of knowledge sources and learning algorithms for word sense disambiguation", "key" : "lee_empirical_2002" }, { "journal" : "Machine Translation Summit {IX}", "pub-type" : "article", "uri" : "urn:1643a29e0dcec290c716f5db340567fe", "pages" : "2", "date" : "2003", "author" : [ "Turian, J. P.", "Shen, L.", "Melamed, I. D." ], "volume" : "100", "keywords" : [ "machine translation", "mt eval" ], "type" : "Publication", "year" : "2003", "label" : "Evaluation of Machine Translation and its Evaluation", "key" : "turian_evaluation_2003" }, { "pub-type" : "inproceedings", "uri" : "urn:5571b1838d4081ec98afa47a51d574e4", "pages" : "345--354", "date" : "2006", "author" : [ "Eguchi, Koji", "Lavrenko, Victor" ], "keywords" : [ "generative models", "machine learning", "opinion mining", "sentiment analysis" ], "year" : "2006", "type" : "Publication", "label" : "Sentiment retrieval using generative models", "key" : "eguchi_sentiment_2006" }, { "publisher" : "{ACM}", "url" : "http://portal.acm.org/citation.cfm?id=1099554.1099713", "booktitle" : "Proceedings of the 14th {ACM} international conference on Information and knowledge management", "pub-type" : "inproceedings", "uri" : "urn:11e183dcbdb6f679a4577eae34513286", "pages" : "617--624", "date" : "2005", "author" : [ "Esuli, Andrea", "Sebastiani, Fabrizio" ], "keywords" : [ "opinion mining", "semantic orientation", "sentiment analysis" ], "doi" : "10.1145/1099554.1099713", "type" : "Publication", "year" : "2005", "abstract" : "Sentiment classification is a recent subdiscipline of text classification which is concerned not with the topic a document is about, but with the opinion it expresses. It has a rich set of applications, ranging from tracking users\' opinions about products or about political candidates as expressed in online forums, to customer relationship management. Functional to the extraction of opinions from text is the determination of the orientation of ``subjective\'\' terms contained in text, i.e. the determination of whether a term that carries opinionated content has a positive or a negative connotation. In this paper we present a new method for determining the orientation of subjective terms. The method is based on the quantitative analysis of the glosses of such terms, i.e. the definitions that these terms are given in on-line dictionaries, and on the use of the resulting term representations for semi-supervised term classification. The method we present outperforms all known methods when tested on the recognized standard benchmarks for this task.", "isbn" : "1-59593-140-6", "label" : "Determining the semantic orientation of terms through gloss classification", "address" : "Bremen, Germany", "key" : "esuli_determiningsemantic_2005" }, { "journal" : "Proceedings of the {HLT-NAACL} 2006 Workshop on Statistical Machine Translation", "pub-type" : "article", "uri" : "urn:0cb60028ac87d8fd2410f007f717a6d6", "pages" : "86--93", "date" : "2006", "author" : [ "Owczarzak, K.", "Groves, D.", "Genabith, J. Van", "Way, A." ], "keywords" : [ "machine translation", "mt eval", "paraphrases" ], "type" : "Publication", "year" : "2006", "label" : "Contextual {Bitext-Derived} Paraphrases in Automatic {MT} Evaluation", "key" : "owczarzak_contextual_2006" }, { "journal" : "Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics", "pub-type" : "article", "uri" : "urn:c8719815c6b71568024143d439a8b1fc", "date" : "2004", "author" : [ "Clark, S.", "Curran, J. R." ], "keywords" : [ "ccg", "log-linear models", "parsing" ], "year" : "2004", "type" : "Publication", "label" : "Parsing the {WSJ} using {CCG} and log-linear models", "key" : "clark_parsingwsj_2004" }, { "journal" : "Proceedings of {ACL}", "pub-type" : "article", "uri" : "urn:f056d8ac679d5695a8793a379c5d890b", "pages" : "320????327", "date" : "2004", "author" : [ "Cahill, A.", "Burke, M.", "{O????Donovan}, R.", "Genabith, J. van", "Way, A." ], "volume" : "4", "keywords" : [ "lfg", "linguistics", "parsing" ], "type" : "Publication", "year" : "2004", "label" : "{Long-Distance} Dependency Resolution in Automatically Acquired {Wide-Coverage} {PCFG-Based} {LFG} Approximations", "key" : "cahill_long-distance_2004" }, { "journal" : "Proceedings of {NAACL} {HLT}", "pub-type" : "article", "uri" : "urn:f1ebd7b81f75fff7ac60d42b17697a5e", "pages" : "41--48", "date" : "2007", "author" : [ "Liu, D.", "Gildea, D." ], "keywords" : [ "machine translation", "mt eval" ], "type" : "Publication", "year" : "2007", "label" : "{Source-Language} Features and Maximum Correlation Training for Machine Translation Evaluation", "key" : "liu_source-language_2007" }, { "publisher" : "Association for Computational Linguistics", "url" : "http://portal.acm.org/citation.cfm?id=1220678", "booktitle" : "Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing", "pub-type" : "inproceedings", "uri" : "urn:0e7f3d976ec1bb5fbb580859726567dd", "pages" : "819--826", "date" : "2005", "author" : [ "Brown, Jonathan C.", "Frishkoff, Gwen A.", "Eskenazi, Maxine" ], "keywords" : [ "{CALL", "question} generation" ], "type" : "Publication", "year" : "2005", "abstract" : "In the {REAP} system, users are automatically provided with texts to read targeted to their individual reading levels. To find appropriate texts, the user\'s vocabulary knowledge must be assessed. We describe an approach to automatically generating questions for vocabulary assessment. Traditionally, these assessments have been hand-written. Using data from {WordNet,} we generate 6 types of vocabulary questions. They can have several forms, including wordbank and multiple-choice. We present experimental results that suggest that these automatically-generated questions give a measure of vocabulary skill that correlates well with subject performance on independently developed human-written questions. In addition, strong correlations with standardized vocabulary tests point to the validity of our approach to automatic assessment of word knowledge.", "label" : "Automatic question generation for vocabulary assessment", "address" : "Vancouver, British Columbia, Canada", "key" : "brown_automatic_2005" }, { "booktitle" : "Workshop on the Question Generation Shared Task and Evaluation Challenge", "pub-type" : "inproceedings", "uri" : "urn:2192172d927f9b2528097d1cfe9da4ab", "date" : "2008", "author" : "Nielsen, R.", "keywords" : "question generation", "comment" : "{\\textless}p{\\textgreater}3 tasks:{\\textless}/p{\\textgreater} {\\textless}ol{\\textgreater} {\\textless}li{\\textgreater}concept selection{\\textless}/li{\\textgreater} {\\textless}li{\\textgreater}question type determination{\\textless}/li{\\textgreater} {\\textless}li{\\textgreater}question construction{\\textless}/li{\\textgreater} {\\textless}/ol{\\textgreater}", "type" : "Publication", "year" : "2008", "label" : "Question Generation: Proposed Challenge Tasks and Their Evaluation", "address" : "Arlington, Virginia, {USA}", "key" : "nielsen_question_2008" }, { "booktitle" : "Workshop on the Question Generation Shared Task and Evaluation Challenge", "pub-type" : "inproceedings", "uri" : "urn:dbc912e0ae64c468cdfb8c5f08c6b3c7", "date" : "2008", "author" : "Vanderwende, L.", "keywords" : "question generation", "year" : "2008", "type" : "Publication", "label" : "The Importance of Being Important: Question Generation", "address" : "Arlington, Virginia, {USA}", "key" : "vanderwende_importance_2008" }, { "booktitle" : "Workshop on the Question Generation Shared Task and Evaluation Challenge", "pub-type" : "inproceedings", "uri" : "urn:fa2b8d31521e6fbfebbadc48368512af", "date" : "2008", "author" : [ "Nielsen, R.", "Buckingham, J.", "Knoll, G.", "Marsh, B.", "Palen, L." ], "type" : "Publication", "year" : "2008", "label" : "A Taxonomy of Questions for Question Generation", "address" : "Arlington, Virginia, {USA}", "key" : "nielsen_taxonomy_2008" }, { "booktitle" : "Proceedings of the {ACL} 2005 The Second Workshop on Building Educational Applications Using Natural Language Processing", "pub-type" : "inproceedings", "uri" : "urn:b7428f73ab86f447f501196cc1539b05", "date" : "2005", "author" : [ "Hoshino, A.", "Nakagawa, H." ], "keywords" : "question generation", "type" : "Publication", "year" : "2005", "label" : "A realtime multiple-choice question generation for language testing: A preliminary study", "key" : "hoshino_realtime_2005" }, { "publisher" : "Association for Computational Linguistics Morristown, {NJ,} {USA}", "booktitle" : "Proceedings of the {COLING/ACL} on Interactive presentation sessions", "pub-type" : "inproceedings", "uri" : "urn:bf2a36fadc16ca8d49c4197b18122a01", "pages" : "1--4", "date" : "2006", "author" : [ "Chen, C. Y.", "Liou, H. C.", "Chang, J. S." ], "keywords" : "question generation", "type" : "Publication", "year" : "2006", "label" : "{FAST:} an automatic generation system for grammar tests", "key" : "chen_fast:automatic_2006" }, { "booktitle" : "Workshop on the Question Generation Shared Task and Evaluation Challenge", "pub-type" : "inproceedings", "uri" : "urn:f212590301868c8bf714d1d9b8ed31fd", "date" : "2008", "author" : [ "Ignatova, Kateryna", "Bernhard, Delphine", "Gurevych, Iryna" ], "type" : "Publication", "year" : "2008", "label" : "Generating high quality questions from low quality questions", "address" : "Arlington, Virginia, {USA}", "key" : "ignatova_generating_2008" }, { "booktitle" : "Workshop on the Question Generation Shared Task and Evaluation Challenge", "pub-type" : "inproceedings", "uri" : "urn:82dd6412b2c3de3a323abfe4dd6d718c", "date" : "2008", "author" : "Gates, Donna", "type" : "Publication", "year" : "2008", "label" : "Generating loop-back strategy questions from expository texts", "address" : "2008", "key" : "gates_generating_2008" }, { "booktitle" : "Workshop on the Question Generation Shared Task and Evaluation Challenge", "pub-type" : "inproceedings", "uri" : "urn:436982e846a808b5993c84576c6b3192", "date" : "2008", "author" : [ "Prasad, Rashmi", "Joshi, Aravind" ], "type" : "Publication", "year" : "2008", "label" : "A discourse-based approach to generating why-questions from texts", "address" : "Arlington, Virginia, {USA}", "key" : "prasad_discourse-based_2008" }, { "booktitle" : "Proceedings of the Workshop on Shared Tasks and Comparative Evaluation in Natural Language Generation", "pub-type" : "inproceedings", "uri" : "urn:1ab487e64b1155c014766e47d3116d2a", "pages" : "20--21", "date" : "2007", "author" : [ "Rus, V.", "Cai, Z.", "Graesser, A. C." ], "type" : "Publication", "year" : "2007", "label" : "Evaluation in Natural Language Generation: The Question Generation Task", "key" : "rus_evaluation_2007" }, { "booktitle" : "Workshop on the Question Generation Shared Task and Evaluation Challenge", "pub-type" : "inproceedings", "uri" : "urn:8000e612f23eaf4022e86c38d8cbacf4", "date" : "2008", "author" : [ "Smith, Noah", "Heilman, Michael", "Hwa, Rebecca" ], "type" : "Publication", "year" : "2008", "label" : "Question Generation as a Competitve Undergraduate Course Project", "key" : "smith_question_2008" }, { "booktitle" : "Proceedings of {ICCE2004}", "pub-type" : "inproceedings", "uri" : "urn:f7f246f52d9c862f276188c6bba1e74b", "pages" : "2--5", "date" : "2003", "author" : [ "Kunichika, H.", "Katayama, T.", "Hirashima, T.", "Takeuchi, A." ], "type" : "Publication", "year" : "2003", "label" : "Automated question generation methods for intelligent English learning systems and its evaluation", "key" : "kunichika_automated_2003" }, { "booktitle" : "Acoustics, Speech and Signal Processing, 1998. Proceedings of the 1998 {IEEE} International Conference on", "pub-type" : "inproceedings", "uri" : "urn:7a0064a4cfbbc66dd700ba821376a78c", "pages" : "805--808 vol.2", "date" : "1998", "author" : [ "Beulen, K.", "Ney, H." ], "volume" : "2", "keywords" : [ "acoustic models", "acoustic signal processing", "across-word phoneme model", "automatic question generation", "decision theory", "decision tree based state tying", "fricatives", "matrix algebra", "pattern classification", "performance", "phoneme clustering algorithm", "phoneme set", "phonetic categories", "phonetic expert", "phonetic questions", "plosives", "pronunciation", "recognition results", "speech recognition", "trees (mathematics)", "triphone {states", "vowels", "Wall} Street Journal data", "within-word phoneme model" ], "doi" : "{10.1109/ICASSP.1998.675387}", "type" : "Publication", "year" : "1998", "abstract" : "Decision tree based state tying uses so-called phonetic questions to assign triphone states to reasonable acoustic models. These phonetic questions are in fact phonetic categories such as vowels, plosives or fricatives. The assumption behind this is that context phonemes which belong to the same phonetic class have a similar influence on the pronunciation of a phoneme. For a new phoneme set, which has to be used, for example, when switching to a different corpus, a phonetic expert is needed to define proper phonetic questions. In this paper a new method is presented which automatically defines good phonetic questions for a phoneme set. This method uses the intermediate clusters from a phoneme clustering algorithm which are reduced to an appropriate number afterwards. Recognition results on the Wall Street Journal data for within-word and across-word phoneme models show competitive performance of the automatically generated questions with our best handcrafted question set", "isbn" : "1520-6149", "label" : "Automatic question generation for decision tree based state tying", "key" : "beulen_automatic_1998" }, { "journal" : "Urbana", "pub-type" : "article", "uri" : "urn:59b004d87663f8c4300a22dda22d4af6", "pages" : "61801", "author" : [ "Titov, I.", "{McDonald}, R." ], "volume" : "51", "type" : "Publication", "label" : "A Joint Model of Text and Aspect Ratings for Sentiment Summarization", "key" : "titov_joint_????" }, { "url" : "http://www2.computer.org/portal/web/csdl/doi/10.1109/ICIS.2008.46", "pub-type" : "inproceedings", "uri" : "urn:0a617d741c48dd555bef6eb0e8b12f50", "date" : "2008", "author" : [ "Kyoomarsi, Farshad", "Khosravi, Hamid", "Eslami, Esfandiar", "Dehkordy, Pooya Khosravyan", "Tajoddin, Asghar" ], "keywords" : [ "fuzzy logic", "summarization" ], "type" : "Publication", "year" : "2008", "label" : "Optimizing Text Summarization Based on Fuzzy Logic", "key" : "kyoomarsi_optimizing_2008" }, { "url" : "http://portal.acm.org/citation.cfm?id=944919.944937", "journal" : "The Journal of Machine Learning Research", "pub-type" : "article", "uri" : "urn:d5b304b79a56d892a48b1c18912c69db", "pages" : "993--1022", "date" : "2003", "author" : [ "Blei, David M.", "Ng, Andrew Y.", "Jordan, Michael I." ], "keywords" : [ "clustering", "document modeling", "latent dirichlet allocation" ], "volume" : "3", "type" : "Publication", "year" : "2003", "abstract" : "We describe latent Dirichlet allocation {(LDA),} a generative probabilistic model for collections of discrete data such as text corpora. {LDA} is a three-level hierarchical Bayesian model, in which each item of a collection is modeled as a finite mixture over an underlying set of topics. Each topic is, in turn, modeled as an infinite mixture over an underlying set of topic probabilities. In the context of text modeling, the topic probabilities provide an explicit representation of a document. We present efficient approximate inference techniques based on variational methods and an {EM} algorithm for empirical Bayes parameter estimation. We report results in document modeling, text classification, and collaborative filtering, comparing to a mixture of unigrams model and the probabilistic {LSI} model.", "label" : "Latent dirichlet allocation", "key" : "blei_latent_2003" }, { "url" : "http://www.pnas.org/content/101/suppl.1/5228.abstract?ck=nck", "booktitle" : "Proceedings of the National Academy of Sciences", "pub-type" : "inproceedings", "uri" : "urn:dc65888acd42e508b622ccee8d676c3a", "date" : "2004-04", "author" : [ "Griffiths, Thomas L.", "Steyvers, Mark" ], "volume" : "101", "month" : "April", "type" : "Publication", "year" : "2004", "abstract" : "A first step in identifying the content of a document is determining which topics that document addresses. We describe a generative model for documents, introduced by Blei, Ng, and Jordan {[Blei,} D. M., Ng, A. Y. \\& Jordan, M. I. (2003) J. Machine Learn. Res. 3, 993-1022], in which each document is generated by choosing a distribution over topics and then choosing each word in the document from a topic selected according to this distribution. We then present a Markov chain Monte Carlo algorithm for inference in this model. We use this algorithm to analyze abstracts from {PNAS} by using Bayesian model selection to establish the number of topics. We show that the extracted topics capture meaningful structure in the data, consistent with the class designations provided by the authors of the articles, and outline further applications of this analysis, including identifying ??????hot topics?????? by examining temporal dynamics and tagging abstracts to illustrate semantic content.", "label" : "Finding scientific topics", "key" : "griffiths_finding_2004" }, { "journal" : "Annals of Applied Statistics", "pub-type" : "article", "uri" : "urn:eee40e8dae135a6d7f66718245fa3e92", "pages" : "17--35", "date" : "2007", "number" : "1", "author" : [ "Blei, D. M.", "Lafferty, J. D." ], "volume" : "1", "type" : "Publication", "year" : "2007", "label" : "A {CORRELATED} {TOPIC} {MODEL} {OF} {SCIENCE}", "key" : "blei_correlated_2007" }, { "label" : "A Uniform Approach to Analogies, Synonyms, Antonyms, and Associations {\\textbar} Publications {\\textbar} {NRC-IIT}", "howpublished" : "http://iit-iti.nrc-cnrc.gc.ca/publications/nrc-50398\\_e.html", "url" : "http://iit-iti.nrc-cnrc.gc.ca/publications/nrc-50398_e.html", "key" : "government_of_canada_uniform_????", "type" : "Publication", "pub-type" : "misc", "author" : "Canada, National Research Council Canada Government of", "uri" : "urn:c475e2d91c62ca368bdea39c9e4d52a4" }, { "publisher" : "{ACM}", "url" : "http://portal.acm.org/citation.cfm?doid=1454008.1454030", "booktitle" : "Proceedings of the 2008 {ACM} conference on Recommender systems", "pub-type" : "inproceedings", "uri" : "urn:6906df0b6316fe2ef7143e2c9aec299c", "pages" : "123--130", "date" : "2008", "author" : [ "Zhang, Mi", "Hurley, Neil" ], "keywords" : [ "accuracy", "diversity", "metrics", "novelty", "recommender system" ], "doi" : "10.1145/1454008.1454030", "type" : "Publication", "year" : "2008", "abstract" : "The primary premise upon which {top-N} recommender systems operate is that similar users are likely to have similar tastes with regard to their product choices. For this reason, recommender algorithms depend deeply on similarity metrics to build the recommendation lists for end-users.", "isbn" : "978-1-60558-093-7", "label" : "Avoiding monotony: improving the diversity of recommendation lists", "address" : "Lausanne, Switzerland", "key" : "zhang_avoiding_2008" }, { "url" : "http://arxiv.org/abs/cs/0703109", "journal" : "cs/0703109", "pub-type" : "article", "uri" : "urn:91f80344923615f6457ac1012c0b6676", "date" : "2007-03", "author" : [ "Kaser, Owen", "Lemire, Daniel" ], "keywords" : "Computer Science - Data Structures and Algorithms", "month" : "March", "type" : "Publication", "year" : "2007", "abstract" : "Tag clouds provide an aggregate of tag-usage statistics. They are typically sent as in-line {HTML} to browsers. However, display mechanisms suited for ordinary text are not ideal for tags, because font sizes may vary widely on a line. As well, the typical layout does not account for relationships that may be known between tags. This paper presents models and algorithms to improve the display of tag clouds that con- sist of in-line {HTML,} as well as algorithms that use nested tables to achieve a more general 2-dimensional layout in which tag relationships are considered. The first algorithms leverage prior work in typesetting and rectangle packing, whereas the second group of algorithms leverage prior work in Electronic Design Automation. Experiments show our algorithms can be efficiently implemented and perform well.", "label" : "{Tag-Cloud} Drawing: Algorithms for Cloud Visualization", "key" : "kaser_tag-cloud_2007" }, { "publisher" : "{ACM}", "url" : "http://portal.acm.org/citation.cfm?id=1390431", "booktitle" : "Proceedings of the 31st annual international {ACM} {SIGIR} conference on Research and development in information retrieval", "pub-type" : "inproceedings", "uri" : "urn:896c6f91d4f9ad091e6297d562e5be70", "pages" : "563--570", "date" : "2008", "author" : [ "Theobald, Martin", "Siddharth, Jonathan", "Paepcke, Andreas" ], "keywords" : [ "high-dimensional similarity search", "inverted index pruning", "optimal partitioning", "stopword signatures" ], "doi" : "10.1145/1390334.1390431", "type" : "Publication", "year" : "2008", "abstract" : "Motivated by our work with political scientists who need to manually analyze large Web archives of news sites, we present {SpotSigs,} a new algorithm for extracting and matching signatures for near duplicate detection in large Web crawls. Our spot signatures are designed to favor natural-language portions of Web pages over advertisements and navigational bars.", "isbn" : "978-1-60558-164-4", "label" : "{SpotSigs:} robust and efficient near duplicate detection in large web collections", "address" : "Singapore, Singapore", "key" : "theobald_spotsigs:_2008" }, { "journal" : "Computer Networks and {ISDN} Systems", "pub-type" : "article", "uri" : "urn:fbb9070eebfd41568b9ac8f3232ba70f", "pages" : "1157--1166", "date" : "1997", "number" : "8-13", "author" : [ "Broder, A. Z.", "Glassman, S. C.", "Manasse, M. S.", "Zweig, G." ], "volume" : "29", "type" : "Publication", "year" : "1997", "label" : "Syntactic clustering of the Web", "key" : "broder_syntactic_1997" }, { "publisher" : "{ACM}", "url" : "http://portal.acm.org/citation.cfm?id=1150402.1150450", "booktitle" : "Proceedings of the 12th {ACM} {SIGKDD} international conference on Knowledge discovery and data mining", "pub-type" : "inproceedings", "uri" : "urn:9ee67b212a33d58b92e0d27ba8157ef2", "pages" : "424--433", "date" : "2006", "author" : [ "Wang, Xuerui", "{McCallum}, Andrew" ], "keywords" : [ "graphical models", "temporal analysis", "topic modeling" ], "doi" : "10.1145/1150402.1150450", "type" : "Publication", "year" : "2006", "abstract" : "This paper presents an {LDA-style} topic model that captures not only the low-dimensional structure of data, but also how the structure changes over time. Unlike other recent work that relies on Markov assumptions or discretization of time, here each topic is associated with a continuous distribution over timestamps, and for each generated document, the mixture distribution over topics is influenced by both word co-occurrences and the document\'s timestamp. Thus, the meaning of a particular topic can be relied upon as constant, but the topics\' occurrence and correlations change significantly over time. We present results on nine months of personal email, 17 years of {NIPS} research papers and over 200 years of presidential state-of-the-union addresses, showing improved topics, better timestamp prediction, and interpretable trends.", "isbn" : "1-59593-339-5", "label" : "Topics over time: a {non-Markov} continuous-time model of topical trends", "address" : "Philadelphia, {PA,} {USA}", "key" : "wang_topics_2006" }, { "url" : "http://www.daniel-lemire.com/fr/abstracts/DIVERSITY2008.html", "pub-type" : [ "unpublished", "Tech Report" ], "uri" : "urn:752219a430510ff1c84a9cca33d9e1b7", "date" : "2008", "author" : [ "Lemire, Daniel", "Downes, Stephen", "Paquet, Sebastien" ], "type" : "Publication", "year" : "2008", "abstract" : "Online communities have become become a crucial ingredient of e-business. Supporting open social networks builds strong brands and provides lasting value to the consumer. One function of the community is to recommend new products and services. Open social networks tend to be resilient, adaptive, and broad, but simplistic recommender systems can be \'gamed\' by members seeking to promote certain products or services. We argue that the gaming is not the failure of the open social network, but rather of the function used by the recommender. To increase the quality and resilience of recommender systems, and provide the user with genuine and novel discoveries, we have to foster diversity, instead of closing down the social networks. Fortunately, software increases the broadcast capacity of each individual, making dense open social networks possible. Numerically, we show that dense social networks encourage diversity. In business terms, dense social networks support a long tail.", "label" : "Diversity in open social networks", "key" : "lemire_diversity_2008" }, { "journal" : "Fuzzy Systems, {IEEE} Transactions on", "pub-type" : "article", "uri" : "urn:647ddbfea35beedb4a83793f7cb39a0b", "pages" : "320--330", "date" : "2008", "number" : "2", "author" : [ "Bargiela, A.", "Pedrycz, W." ], "volume" : "16", "doi" : "{10.1109/TFUZZ.2007.905912}", "type" : "Publication", "year" : "2008", "abstract" : "Human-centered information processing has been pioneered by Zadeh through his introduction of the concept of fuzzy sets in the mid 1960s. The insights that were afforded through this formalism have led to the development of the granular computing {(GrC)} paradigm in the late 1990s. Subsequent research has highlighted the fact that many founding principles of {GrC} have, in fact, been adopted in other information-processing paradigms and, indeed, in the context of various scientific methodologies. This study expands on our earlier research exploring the foundations of {GrC} and casting it as a structured combination of algorithmic and non- algorithmic information processing that mimics human, intelligent synthesis of knowledge from information.", "label" : "Toward a Theory of Granular Computing for {Human-Centered} Information Processing", "issn" : "1063-6706", "key" : "bargiela_towardtheory_2008" }, { "id" : "92cf486da9a31c45ca2173362437fe82", "journal" : "Fuzzy Systems, {IEEE} Transactions on", "pub-type" : "article", "uri" : "urn:92cf486da9a31c45ca2173362437fe82", "pages" : "320--330", "date" : "2008", "number" : "2", "author" : [ "Bargiela, A.", "Pedrycz, W." ], "volume" : "16", "doi" : "{10.1109/TFUZZ.2007.905912}", "type" : "Publication", "year" : "2008", "abstract" : "Human-centered information processing has been pioneered by Zadeh through his introduction of the concept of fuzzy sets in the mid 1960s. The insights that were afforded through this formalism have led to the development of the granular computing {(GrC)} paradigm in the late 1990s. Subsequent research has highlighted the fact that many founding principles of {GrC} have, in fact, been adopted in other information-processing paradigms and, indeed, in the context of various scientific methodologies. This study expands on our earlier research exploring the foundations of {GrC} and casting it as a structured combination of algorithmic and non- algorithmic information processing that mimics human, intelligent synthesis of knowledge from information.", "label" : "Toward a Theory of Granular Computing for {Human-Centered} Information Processing", "issn" : "1063-6706", "key" : "bargiela_towardtheory_2008-1" }, { "id" : "10e9f325a0a6d9d598a91fdd11db6a43", "journal" : "Fuzzy Systems, {IEEE} Transactions on", "pub-type" : "article", "uri" : "urn:10e9f325a0a6d9d598a91fdd11db6a43", "pages" : "320--330", "date" : "2008", "number" : "2", "author" : [ "Bargiela, A.", "Pedrycz, W." ], "volume" : "16", "type" : "Publication", "year" : "2008", "label" : "Toward a Theory of Granular Computing for {Human-Centered} Information Processing", "key" : "bargiela_towardtheory_2008-2" }, { "label" : "Data Mining, Rough Sets and Granular Computing", "key" : "lin_data_????", "type" : "Publication", "pub-type" : "article", "author" : [ "Lin, T. Y.", "Yao, Y. Y.", "Zadeh, L. A." ], "uri" : "urn:1539bcca9aaffb9fecb22935b2f15442" }, { "label" : "{FUZZY} {SETS} {AND} {INFORMATION} {GRANULARITY}", "key" : "zadeh_fuzzy_????", "type" : "Publication", "pub-type" : "article", "author" : "Zadeh, L. A.", "uri" : "urn:8264530f9fc49a3900f6b9792877f13a" }, { "publisher" : "{ACM}", "url" : "http://portal.acm.org/citation.cfm?id=1277845", "booktitle" : "Proceedings of the 30th annual international {ACM} {SIGIR} conference on Research and development in information retrieval", "pub-type" : "inproceedings", "uri" : "urn:21c17065fbfaf456c564b9c62c1dbe3d", "pages" : "607--614", "date" : "2007", "author" : [ "Liu, Yang", "Huang, Xiangji", "An, Aijun", "Yu, Xiaohui" ], "keywords" : [ "autoregressive model", "blog", "sentiment mining" ], "doi" : "10.1145/1277741.1277845", "type" : "Publication", "year" : "2007", "abstract" : "Due to its high popularity, Weblogs (or blogs in short) present a wealth of information that can be very helpful in assessing the general public\'s sentiments and opinions. In this paper, we study the problem of mining sentiment information from blogs and investigate ways to use such information for predicting product sales performance. Based on an analysis of the complex nature of sentiments, we propose Sentiment {PLSA} {(S-PLSA),} in which a blog entry is viewed as a document generated by a number of hidden sentiment factors. Training an {S-PLSA} model on the blog data enables us to obtain a succinct summary of the sentiment information embedded in the blogs. We then present {ARSA,} an autoregressive sentiment-aware model, to utilize the sentiment information captured by {S-PLSA} for predicting product sales performance. Extensive experiments were conducted on a movie data set. We compare {ARSA} with alternative models that do not take into account the sentiment information, as well as a model with a different feature selection method. Experiments confirm the effectiveness and superiority of the proposed approach.", "isbn" : "978-1-59593-597-7", "label" : "{ARSA:} a sentiment-aware model for predicting sales performance using blogs", "address" : "Amsterdam, The Netherlands", "key" : "liu_arsa:sentiment-aware_2007" }, { "booktitle" : "Computational Intelligence for Financial Engineering, {1995.,Proceedings} of the {IEEE/IAFE} 1995", "pub-type" : "inproceedings", "uri" : "urn:5e6e34642a3a601577a29c39cbf4fe69", "pages" : "146--150", "date" : "1995", "author" : "Piche, {S.W.}", "keywords" : [ "capital markets", "data visualisation", "double moving average trading systems", "financial data processing", "foreign currency spot market", "foreign exchange trading", "moving average processes", "plotting", "returns", "time series", "trading rules", "trend visualization" ], "doi" : "{10.1109/CIFER.1995.495268}", "type" : "Publication", "year" : "1995", "abstract" : "Double moving averages are commonly used to identify trends within capital markets. In this paper, a novel analysis technique is presented which is based upon plotting the returns associated with thousands of different double moving average trading rules for a time series. The resulting plots are useful for gaining an understanding of the trends contained within the time series. The analysis technique, which is referred to as trend visualization, is also useful for selecting the appropriate parameters for double moving average trading systems. In this paper, the technique is used to investigate trends within the foreign currency spot market", "label" : "Trend visualization", "key" : "piche_trend_1995" }, { "booktitle" : "Proceedings of {AAAI}", "pub-type" : "inproceedings", "uri" : "urn:c73c9e0ac7de4dcc3f05eeb6d4990938", "pages" : "12--15", "date" : "2003", "author" : [ "Beineke, P.", "Hastie, T.", "Manning, C.", "Vaithyanathan, S." ], "type" : "Publication", "year" : "2003", "label" : "An exploration of sentiment summarization", "key" : "beineke_exploration_2003" }, { "publisher" : "{ACM}", "url" : "http://portal.acm.org/citation.cfm?id=1099714&dl=GUIDE,", "booktitle" : "Proceedings of the 14th {ACM} international conference on Information and knowledge management", "pub-type" : "inproceedings", "uri" : "urn:1969479f04311a24d71c122d0e26f3f8", "pages" : "625--631", "date" : "2005", "author" : [ "Whitelaw, Casey", "Garg, Navendu", "Argamon, Shlomo" ], "keywords" : [ "appraisal theory", "opinion mining", "review classification", "sentiment analysis", "shallow parsing", "text classification" ], "doi" : "10.1145/1099554.1099714", "type" : "Publication", "year" : "2005", "abstract" : "Little work to date in sentiment analysis (classifying texts by `positive\' or `negative\' orientation) has attempted to use fine-grained semantic distinctions in features used for classification. We present a new method for sentiment classification based on extracting and analyzing appraisal groups such as ``very good\'\' or ``not terribly funny\'\'. An appraisal group is represented as a set of attribute values in several task-independent semantic taxonomies, based on Appraisal Theory. Semi-automated methods were used to build a lexicon of appraising adjectives and their modifiers. We classify movie reviews using features based upon these taxonomies combined with standard ``bag-of-words\'\' features, and report state-of-the-art accuracy of 90.2\\%. In addition, we find that some types of appraisal appear to be more significant for sentiment classification than others.", "isbn" : "1-59593-140-6", "label" : "Using appraisal groups for sentiment analysis", "address" : "Bremen, Germany", "key" : "whitelaw_using_2005" }, { "publisher" : "{ACM}", "url" : "http://portal.acm.org/citation.cfm?id=1183614.1183625", "id" : "82ad8589c665e84c0f8a1ccbbd5a1ddd", "booktitle" : "Proceedings of the 15th {ACM} international conference on Information and knowledge management", "pub-type" : "inproceedings", "uri" : "urn:82ad8589c665e84c0f8a1ccbbd5a1ddd", "pages" : "43--50", "date" : "2006", "author" : [ "Zhuang, Li", "Jing, Feng", "Zhu, {Xiao-Yan}" ], "doi" : "10.1145/1183614.1183625", "type" : "Publication", "year" : "2006", "abstract" : "With the flourish of the Web, online review is becoming a more and more useful and important information resource for people. As a result, automatic review mining and summarization has become a hot research topic recently. Different from traditional text summarization, review mining and summarization aims at extracting the features on which the reviewers express their opinions and determining whether the opinions are positive or negative. In this paper, we focus on a specific domain - movie review. A multi-knowledge based approach is proposed, which integrates {WordNet,} statistical analysis and movie knowledge. The experimental results show the effectiveness of the proposed approach in movie review mining and summarization.", "isbn" : "1-59593-433-2", "label" : "Movie review mining and summarization", "address" : "Arlington, Virginia, {USA}", "key" : "zhuang_movie_2006-1" }, { "publisher" : "{ACM}", "url" : "http://portal.acm.org/citation.cfm?id=1183614.1183625", "id" : "52d076e695c8f3f504b9e94a41a59ffb", "booktitle" : "Proceedings of the 15th {ACM} international conference on Information and knowledge management", "pub-type" : "inproceedings", "uri" : "urn:52d076e695c8f3f504b9e94a41a59ffb", "pages" : "43--50", "date" : "2006", "author" : [ "Zhuang, Li", "Jing, Feng", "Zhu, {Xiao-Yan}" ], "doi" : "10.1145/1183614.1183625", "type" : "Publication", "year" : "2006", "abstract" : "With the flourish of the Web, online review is becoming a more and more useful and important information resource for people. As a result, automatic review mining and summarization has become a hot research topic recently. Different from traditional text summarization, review mining and summarization aims at extracting the features on which the reviewers express their opinions and determining whether the opinions are positive or negative. In this paper, we focus on a specific domain - movie review. A multi-knowledge based approach is proposed, which integrates {WordNet,} statistical analysis and movie knowledge. The experimental results show the effectiveness of the proposed approach in movie review mining and summarization.", "isbn" : "1-59593-433-2", "label" : "Movie review mining and summarization", "address" : "Arlington, Virginia, {USA}", "key" : "zhuang_movie_2006-2" }, { "publisher" : "{ACM} Press New York, {NY,} {USA}", "id" : "c29df78750566ccc083ca72ad65f5745", "booktitle" : "Proceedings of the 15th {ACM} international conference on Information and knowledge management", "pub-type" : "inproceedings", "uri" : "urn:c29df78750566ccc083ca72ad65f5745", "pages" : "43--50", "date" : "2006", "author" : [ "Zhuang, L.", "Jing, F.", "Zhu, X. Y." ], "type" : "Publication", "year" : "2006", "label" : "Movie review mining and summarization", "key" : "zhuang_movie_2006-3" }, { "booktitle" : "Proceedings of the {AAAI} Spring Symposium on Computational Approaches to Weblogs", "pub-type" : "inproceedings", "uri" : "urn:591970683c5ddf687351ac3fe28e5121", "date" : "2006", "author" : [ "Mihalcea, R.", "Liu, H." ], "type" : "Publication", "year" : "2006", "label" : "A corpus-based approach to finding happiness", "key" : "mihalcea_corpus-based_2006" }, { "booktitle" : "{ANNUAL} {MEETING-ASSOCIATION} {FOR} {COMPUTATIONAL} {LINGUISTICS}", "pub-type" : "inproceedings", "uri" : "urn:a11f8780c128c07a8233122cab865d98", "pages" : "1065", "date" : "2006", "author" : [ "Wiebe, J.", "Mihalcea, R." ], "volume" : "44", "type" : "Publication", "year" : "2006", "label" : "Word Sense and Subjectivity", "key" : "wiebe_word_2006" }, { "label" : "{DiscLDA:} Discriminative Learning for Dimensionality Reduction and Classification", "key" : "lacoste-julien_disclda:_????", "type" : "Publication", "pub-type" : "article", "author" : [ "{Lacoste-Julien}, S.", "Sha, F.", "Jordan, M. I." ], "uri" : "urn:6f5958099b43491f3ffaa7adc8e39db6" }, { "publisher" : "{VLDB} Endowment", "url" : "http://portal.acm.org/citation.cfm?id=1083658", "booktitle" : "Proceedings of the 31st international conference on Very large data bases", "pub-type" : "inproceedings", "uri" : "urn:95f591295b67eea3721798c48494723e", "pages" : "553--564", "date" : "2005", "author" : [ "Stonebraker, Mike", "Abadi, Daniel J.", "Batkin, Adam", "Chen, Xuedong", "Cherniack, Mitch", "Ferreira, Miguel", "Lau, Edmond", "Lin, Amerson", "Madden, Sam", "{O\'Neil}, Elizabeth", "{O\'Neil}, Pat", "Rasin, Alex", "Tran, Nga", "Zdonik, Stan" ], "type" : "Publication", "year" : "2005", "abstract" : "This paper presents the design of a read-optimized relational {DBMS} that contrasts sharply with most current systems, which are write-optimized. Among the many differences in its design are: storage of data by column rather than by row, careful coding and packing of objects into storage including main memory during query processing, storing an overlapping collection of column-oriented projections, rather than the current fare of tables and indexes, a non-traditional implementation of transactions which includes high availability and snapshot isolation for read-only transactions, and the extensive use of bitmap indexes to complement B-tree {structures.We} present preliminary performance data on a subset of {TPC-H} and show that the system we are building, {C-Store,} is substantially faster than popular commercial products. Hence, the architecture looks very encouraging.", "isbn" : "1-59593-154-6", "label" : "C-store: a column-oriented {DBMS}", "address" : "Trondheim, Norway", "key" : "stonebraker_c-store:column-oriented_2005" }, { "publisher" : "{ACM}", "url" : "http://portal.acm.org/citation.cfm?id=1376713", "booktitle" : "Proceedings of the 2008 {ACM} {SIGMOD} international conference on Management of data", "pub-type" : "inproceedings", "uri" : "urn:e304e4b559ff0d0b6e7c5b28198c2432", "pages" : "981--992", "date" : "2008", "author" : [ "Harizopoulos, Stavros", "Abadi, Daniel J.", "Madden, Samuel", "Stonebraker, Michael" ], "keywords" : [ "dbms architecture", "main memory transaction processing", "oltp", "online transaction processing" ], "doi" : "10.1145/1376616.1376713", "type" : "Publication", "year" : "2008", "abstract" : "Online Transaction Processing {(OLTP)} databases include a suite of features - disk-resident B-trees and heap files, locking-based concurrency control, support for multi-threading - that were optimized for computer technology of the late 1970\'s. Advances in modern processors, memories, and networks mean that today\'s computers are vastly different from those of 30 years ago, such that many {OLTP} databases will now fit in main memory, and most {OLTP} transactions can be processed in milliseconds or less. Yet database architecture has changed little.", "isbn" : "978-1-60558-102-6", "label" : "{OLTP} through the looking glass, and what we found there", "address" : "Vancouver, Canada", "key" : "harizopoulos_oltp_2008" }, { "booktitle" : "Proceedings of {VLDB}", "pub-type" : "inproceedings", "uri" : "urn:bf194995dfb817a6afabdf4d6cd2d0e5", "pages" : "1496--1499", "date" : "2008", "author" : [ "Kallman, Robert", "Kimura, Hideaki", "Natkins, Jonathan", "Pavlo, Andrew", "Rasin, Alex", "Zdonik, Stan", "Jones, Evan", "Zhang, Yang", "Madden, Samuel", "Stonebraker, Michael", "Hugg, John", "Abadi, Daniel" ], "type" : "Publication", "year" : "2008", "label" : "{H-Store:} A {High-Performance,} Distributed Main Memory Transaction Processing System", "key" : "kallman_h-store:high-performance_2008" }, { "url" : "http://portal.acm.org/citation.cfm?doid=146370.146380", "journal" : "{ACM} Comput. Surv.", "pub-type" : "article", "uri" : "urn:fcaa2917c228557b00943209187d8f51", "pages" : "377--439", "date" : "1992", "number" : "4", "author" : "Kukich, Karen", "keywords" : [ "context-dependent spelling correction", "grammar checking", "n-gram analysis", "natural-language-processing models", "neural net classifiers", "optical character recognition (ocr)", "spell checking", "spelling error detection", "spelling error patterns", "statistical-language models", "word recognition and correction" ], "volume" : "24", "doi" : "10.1145/146370.146380", "type" : "Publication", "year" : "1992", "abstract" : "Research aimed at correcting words in text has focused on three progressively more difficult problems:(1) nonword error detection; (2) isolated-word error correction; and (3) context-dependent work correction. In response to the first problem, efficient pattern-matching and n-gram analysis techniques have been developed for detecting strings that do not appear in a given word list. In response to the second problem, a variety of general and application-specific spelling correction techniques have been developed. Some of them were based on detailed studies of spelling error patterns. In response to the third problem, a few experiments using natural-language-processing tools or statistical-language models have been carried out. This article surveys documented findings on spelling error patterns, provides descriptions of various nonword detection and isolated-word error correction techniques, reviews the state of the art of context-dependent word correction techniques, and discusses research issues related to all three areas of automatic error correction in text.", "label" : "Technique for automatically correcting words in text", "key" : "kukich_technique_1992" }, { "url" : "http://dx.doi.org/10.1007/978-3-540-75867-9_37", "booktitle" : "Computer Aided Systems Theory ?????? {EUROCAST} 2007", "pub-type" : "inbook", "uri" : "urn:cfbcebb18a70c8b6907ae202c0ab1005", "pages" : "290--296", "date" : "2007", "author" : [ "Otero, J.", "Gra????a, J.", "Vilares, M." ], "type" : "Publication", "year" : "2007", "abstract" : "Spelling correction is commonly a critical task for a variety of {NLP} tools. Some systems assist users by offering a set of possible corrections for a given misspelt word. An automatic spelling correction system would be able to choose only one or, at least, to rank them according to a certain criterion. We present a dynamic framework which allows us to combine spelling correction and {Part-of-Speech} tagging tasks in an efficient way. The result is a system capable of ranking the set of possible corrections taking the context of the erroneous words into account.", "label" : "Contextual Spelling Correction", "key" : "otero_contextual_2007" }, { "journal" : "Natural Language Engineering", "pub-type" : "article", "uri" : "urn:638ce309a5a7a37fb381b4c91fc6b12b", "pages" : "87--111", "date" : "2005", "number" : "01", "author" : [ "{HIRST}, G.", "{BUDANITSKY}, A." ], "volume" : "11", "type" : "Publication", "year" : "2005", "label" : "Correcting real-word spelling errors by restoring lexical cohesion", "key" : "hirst_correcting_2005" }, { "url" : "http://dx.doi.org/10.1007/978-3-540-78135-6_52", "booktitle" : "Computational Linguistics and Intelligent Text Processing", "pub-type" : "inbook", "uri" : "urn:3381e4b9948344975e9ebcef3aa59d57", "pages" : "605--616", "date" : "2008", "author" : [ "{Wilcox-O??????Hearn}, Amber", "Hirst, Graeme", "Budanitsky, Alexander" ], "type" : "Publication", "year" : "2008", "abstract" : "The trigram-based noisy-channel model of real-word spelling-error correction that was presented by Mays, Damerau, and Mercer in 1991 has never been adequately evaluated or compared with other methods. We analyze the advantages and limitations of the method, and present a new evaluation that enables a meaningful comparison with the {WordNet-based} method of Hirst and Budanitsky. The trigram method is found to be superior, even on content words. We then show that optimizing over sentences gives better results than variants of the algorithm that optimize over fixed-length windows.", "label" : "{Real-Word} Spelling Correction with Trigrams: A Reconsideration of the Mays, Damerau, and Mercer Model", "key" : "wilcox-ohearn_real-word_2008" }, { "url" : "http://dx.doi.org/10.1007/978-3-540-70939-8_55", "booktitle" : "Computational Linguistics and Intelligent Text Processing", "pub-type" : "inbook", "uri" : "urn:a4d5829a297cf0740e87a2e14eecc5a5", "pages" : "623--633", "date" : "2007", "author" : [ "Fossati, Davide", "Eugenio, Barbara Di" ], "type" : "Publication", "year" : "2007", "abstract" : "This paper addresses the problem of real-word spell checking, i.e., the detection and correction of typos that result in real words of the target language. This paper proposes a methodology based on a mixed trigrams language model. The model has been implemented, trained, and tested with data from the Penn Treebank. The approach has been evaluated in terms of hit rate, false positive rate, and coverage. The experiments show promising results with respect to the hit rates of both detection and correction, even though the false positive rate is still high.", "label" : "A Mixed Trigrams Approach for Context Sensitive Spell Checking", "key" : "fossati_mixed_2007" }, { "journal" : "Computational Linguistics", "pub-type" : "article", "uri" : "urn:a512ad19037b37cd0a4a07425d2a3c7d", "pages" : "73--89", "date" : "1996", "number" : "1", "author" : "Oflazer, K.", "volume" : "22", "type" : "Publication", "year" : "1996", "label" : "Error-tolerant finite-state recognition with applications to morphological analysis and spelling correction", "key" : "oflazer_error-tolerant_1996" }, { "publisher" : "Association for Computational Linguistics Morristown, {NJ,} {USA}", "booktitle" : "Proceedings of the 38th Annual Meeting on Association for Computational Linguistics", "pub-type" : "inproceedings", "uri" : "urn:6dba9d31dd062cda746a150f3a74ce23", "pages" : "286--293", "date" : "2000", "author" : [ "Brill, E.", "Moore, R. C." ], "year" : "2000", "type" : "Publication", "label" : "An improved error model for noisy channel spelling correction", "key" : "brill_improved_2000" }, { "label" : "Probability Scoring for Spelling Correction", "key" : "church_probability_????", "type" : "Publication", "pub-type" : "article", "author" : [ "Church, K. W.", "Gale, W. A." ], "uri" : "urn:c6e59f9457c523c725829e0f2978e09e" }, { "journal" : "Information processing \\& management", "pub-type" : "article", "uri" : "urn:89c0d00a6e05878ed31412ca1bd82b4d", "pages" : "517--522", "date" : "1991", "number" : "5", "author" : [ "{MAYS}, E.", "{DAMEREAU}, {FJ}", "{MERCER}, {RL}" ], "volume" : "27", "type" : "Publication", "year" : "1991", "label" : "Context based spelling correction", "key" : "mays_context_1991" }, { "publisher" : "{ISCA}", "booktitle" : "Ninth International Conference on Spoken Language Processing", "pub-type" : "inproceedings", "uri" : "urn:2dbe6404557d3fb6154624310eb47575", "date" : "2006", "author" : [ "Camelin, N.", "Damnati, G.", "Bechet, F.", "Mori, R. D." ], "type" : "Publication", "year" : "2006", "label" : "Opinion Mining in a Telephone Survey Corpus", "key" : "camelin_opinion_2006" }, { "label" : "Soderland, Stephen", "type" : "Author", "uri" : "urn:pg:53877ed34aaec02d54a90c537005c484a2f37d94:Soderland%2C+Stephen", "original-name" : "Stephen Soderland", "last-name" : "Soderland" }, { "label" : "Khosravi, Hamid", "type" : "Author", "uri" : "urn:pg:53877ed34aaec02d54a90c537005c484a2f37d94:Khosravi%2C+Hamid", "original-name" : "Hamid Khosravi", "last-name" : "Khosravi" }, { "label" : "Amig????, E.", "type" : "Author", "uri" : "urn:pg:53877ed34aaec02d54a90c537005c484a2f37d94:Amig%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%2C+E.", "original-name" : "E. Amig????", "last-name" : "Amig????" }, { "label" : "Collier, N.", "type" : "Author", "uri" : "urn:pg:53877ed34aaec02d54a90c537005c484a2f37d94:Collier%2C+N.", "original-name" : "N. Collier", "last-name" : "Collier" }, { "label" : "Brockett, C.", "type" : "Author", "uri" : "urn:pg:53877ed34aaec02d54a90c537005c484a2f37d94:Brockett%2C+C.", "original-name" : "C. Brockett", "last-name" : "Brockett" }, { "label" : "Jing, F.", "type" : "Author", "uri" : "urn:pg:53877ed34aaec02d54a90c537005c484a2f37d94:Jing%2C+F.", "original-name" : "F. Jing", "last-name" : "Jing" }, { "label" : "Fahrni, A.", "type" : "Author", "uri" : "urn:pg:53877ed34aaec02d54a90c537005c484a2f37d94:Fahrni%2C+A.", "original-name" : "A. Fahrni", "last-name" : "Fahrni" }, { "label" : "Etzioni, Oren", "type" : "Author", "uri" : "urn:pg:53877ed34aaec02d54a90c537005c484a2f37d94:Etzioni%2C+Oren", "original-name" : "Oren Etzioni", "last-name" : "Etzioni" }, { "label" : "Rasin, Alex", "type" : "Author", "uri" : "urn:pg:53877ed34aaec02d54a90c537005c484a2f37d94:Rasin%2C+Alex", "original-name" : "Alex Rasin", "last-name" : "Rasin" }, { "label" : "Pennock, David M.", "type" : "Author", "uri" : "urn:pg:53877ed34aaec02d54a90c537005c484a2f37d94:Pennock%2C+David+M.", "original-name" : "David M. Pennock", "last-name" : "Pennock" }, { "label" : "Siddharth, Jonathan", "type" : "Author", "uri" : "urn:pg:53877ed34aaec02d54a90c537005c484a2f37d94:Siddharth%2C+Jonathan", "original-name" : "Jonathan Siddharth", "last-name" : "Siddharth" }, { "label" : "Bargiela, A.", "type" : "Author", "uri" : "urn:pg:53877ed34aaec02d54a90c537005c484a2f37d94:Bargiela%2C+A.", "original-name" : "A. 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