This chapter provides an overview of research to date in knowledge-based word sense disambiguation. It outlines the main knowledge-intensive methods devised so far for automatic sense tagging: 1) methods using contextual overlap with respect to dictionary definitions, 2) methods based on similarity measures computed on semantic networks, 3) selectional preferences as a means of constraining the possible meanings of words in a given context, and 4) heuristic-based methods that rely on properties of human language including the most frequent sense, one sense per discourse, and one sense per collocation.
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References
Agirre, Eneko & German Rigau. 1996. Word sense disambiguation using conceptual density. Proceedings of the International Conference on Computational Linguistics (COLING), Copenhagen, Denmark, 16-22.
Agirre, Eneko & David Martínez. 2001. Learning class-to-class selectional references. Proceedings of the Conference on Natural Language Learning, Toulouse, France, 15-22.
Banerjee, Sid & Ted Pedersen, 2002. An adapted Lesk algorithm for word sense disambiguation using WordNet. Proceedings of the Conference on Computational Linguistics and Intelligent Text Processing (CICLING), exico City, Mexico, 136-145.
Brin, Sergei & Larry Page. 1998. The anatomy of a large-scale hypertextual Web search engine Computer Networks and ISDN Systems, 30(1-7): 107-117.
Brockmann, Carsten & Mirella Lapata. 2003. Evaluating and combining approaches to selectional preference acquisition. Proceedings of the European Association for Computational Linguistics (EACL), Budapest, Hungary, 27-34.
Budanitsky, Alex & Graeme Hirst, 2001. Semantic distance in WordNet: An experimental, application-oriented evaluation of five measures. Proceedings of the NAACL Workshop on WordNet and Other Lexical Resources, ittsburgh, U.S.A., 29-34.
Ciaramita, Massimiliano & Mark Johnson. 2000. Explaining away ambiguity: Learning verb selectional preference with Bayesian networks. Proceedings of7 See the comparative evaluations of supervised and unsupervised systems participating in Senseval in Chapter 8 (Sect. 8.5.1). the International Conference on Computational Linguistics (COLING), Saarbrucken, Germany, 187-193.
Cowie, Jim, Joe A. Guthrie & Louise Guthrie. 1992. Lexical disambiguation using simulated annealing. Proceedings of the International Conference on Computational Linguistics (COLING), Nantes, France, 157-161.
Diab, Mona & Philip Resnik. 2002. An unsupervised method for word sense tagging using parallel corpora. Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL), Philadelphia, U.S.A., 255-262.
Edmonds, Philip. 2005. Lexical disambiguation. The Elsevier Encyclopedia of Language and Linguistics, 2nd Ed., ed. by Keith Brown, 607-23. Oxford: Elsevier.
Erkan, Güneú & Dragomir R. Radev. 2004. Lexrank: Graph-based centrality as salience in text summarization. Journal of Artificial Intelligence Research, 22: 457-479.
Fernandez-Amoros, David, Julio Gonzalo & Felisa Verdejo. 2001. The UNED system at Senseval-2. Proceedings of Senseval-2: Second International Workshop on Evaluating Word Sense Disambiguation Systems, Toulouse, France, 75-78.
Galley, Michel & Kathy McKeown. 2003. Improving word sense disambiguation in lexical chaining. Proceedings of the International Joint Conference in Artificial Intelligence (IJCAI), Acapulco, Mexico, 1486-1488.
Gale, William, Ken Church & David Yarowsky. 1992a. Estimating upper and lower bounds on the performance of word-sense disambiguation programs. Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL), Newark, U.S.A., 249-256.
Gale, William, Ken Church & David Yarowsky. 1992b. One sense per discourse. Proceedings of the DARPA Speech and Natural Language Workshop, New York, U.S.A, 233-237.
Halliday, Michael & Ruqaiya Hasan. 1976. Cohesion in English. London: Longman.
Hirst, Graeme & David St-Onge. 1998. Lexical chains as representations of context in the detection and correction of malaproprisms. In WordNet: An electronic lexical database, ed. by Christiane Fellbaum, 305-332. Massachusetts, U.S.A.: MIT Press.
Jiang, Jian & David Conrath. 1997. Semantic similarity based on corpus statistics and lexical taxonomy. Proceedings of the International Conference on Research in Computational Linguistics, Taipei, Taiwan.
Kilgarriff, Adam & Joseph Rosenzweig. 2000. English SENSEVAL: Report and results. Proceedings of the International Conference on Language Resources and Evaluations (LREC), Athens, Greece, 1239-1244.
Kilgarriff, Adam. 2001. English lexical sample task description. Proceedings of Senseval-2: Second International Workshop on Evaluating Word Sense Disambiguation Systems, Toulouse, France, 17-20.
Krovetz, Robert. 1998. More than one sense per discourse. Proceedings of the Workshop on Evaluating Word Sense Disambiguation Systems (SENSEVAL- 1), Sussex, England.
Leacock, Claudia, Martin Chodorow & George A. Miller. 1998. Using corpus statistics and WordNet relations for sense identification. Computational Linguistics, 24(1): 147-165.
Lesk, Michael. 1986. Automatic sense disambiguation using machine readable dictionaries: How to tell a pine cone from an ice cream cone. Proceedings of the ACM-SIGDOC Conference, Toronto, Canada, 24-26.
Li, Hang & Naoki Abe. 1998. Generalizing case frames using a thesaurus and the MDL principle. Computational Linguistics, 24(2): 217-244.
Lin, Dekang. 1998. An information theoretic definition of similarity. Proceedings of the International Conference on Machine Learning, Madison, U.S.A., 296-304.
Litkowski, Ken. 2001. Use of machine readable dictionaries for word sense disambiguation in Senseval-2. Proceedings of Senseval-2: Second International Workshop on Evaluating Word Sense Disambiguation Systems, Toulouse, France, 107-110.
Magnini, Bernardo, Carlo Strapparava, Giovanni Pezzulo & Alfio Gliozzo. 2001. Using domain information for word sense disambiguation. Proceedings of Senseval-2: Second International Workshop on Evaluating Word Sense Disambiguation Systems, Toulouse, France, 111-114.
Martínez, David & Eneko Agirre. 2000. One sense per collocation and genre/topic variations. Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), Hong Kong, 207-215.
McCarthy, Diana, John Carroll & Judita Preiss. 2001. Disambiguating noun and verb senses using automatically acquired selectional preferences. Proceedings of Senseval-2: Second International Workshop on Evaluating Word Sense Disambiguation Systems, Toulouse, France, 119-122.
McCarthy, Diana, and John Carroll. 2003. Disambiguating nouns, verbs and adjectives using automatically acquired selectional preferences. Computational Linguistics, 29(4): 639-654.
McCarthy, Diana, Robert Koeling, Julie Weeds & John Carroll. 2004. Finding predominant senses in untagged text. Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL), Barcelona, Spain, 280-287.
Mihalcea, Rada & Dan Moldovan. 1999. A method for word sense disambiguation of unrestricted text. Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL), Maryland, U.S.A., 152-158.
Mihalcea, Rada & Dan Moldovan. 2000. An iterative approach to word sense disambiguation. Proceedings of Florida Artificial Intelligence Research Society, Orlando, U.S.A., 219-223.
Mihalcea, Rada. 2005. Large vocabulary unsupervised word sense disambiguation with graph-based algorithms for sequence data labeling. Proceedings of the Joint Human Language Technology and Empirical Methods in Natural Language Processing Conference (HLT/EMNLP), Vancouver, Canada, 411-418.
Miller, George, Martin Chodorow, Shari Landes, Claudia Leacock & Robert Thomas. 1994. Using a semantic concordance for sense identification. Proceedings of the Fourth ARPA Human Language Technology Workshop, 303-308.
Miller, George. 1995. Wordnet: A lexical database. Communications of the ACM, 38(11): 39-41.
Navigli, Roberto & Paola Velardi. 2004. Structural semantic interconnection: A knowledge-based approach to word sense disambiguation. Proceedings of Senseval-3: Third International Workshop on the Evaluation of Systems for the Semantic Analysis of Text, Barcelona, Spain, 179-182.
Okumura, Manabu & Takeo Honda. 1994. Word sense disambiguation and text segmentation based on lexical cohesion. Proceedings of the International Conference on Computational Linguistics (COLING), Kyoto, Japan, 755-761.
Patwardhan, Sid, Satanjeev Banerjee & Ted Pedersen. 2003. Using measures of semantic relatedeness for word sense disambiguation. Proceedings of the Conference on Computational Linguistics and Intelligent Text Processing (CICLING), Mexico City, Mexico, 241-257.
Rada, Roy, Hafedh Mili, Ellen Bicknell & Maria Blettner. 1989. Development and application of a metric on semantic nets. IEEE Transactions on Systems, Man, and Cybernetics, 19(1): 17-30.
Resnik, Philip. 1993. Selection and information: A class-based approach to lexical relationships. Ph.D. Thesis, University of Pennsylvania.
Resnik, Philip. 1995. Using information content to evaluate semantic similarity. Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), Montreal, Canada, 448-453.
Resnik, Philip. 1997. Selectional preference and sense disambiguation. Proceedings of ACL Workshop on Tagging Text with Lexical Semantics, Why, What and How? Washington, U.S.A., 52-57.
Resnik, Philip & David Yarowsky. 1999. Distinguishing systems and distinguishing senses: New evaluation methods for word sense disambiguation. Natural Language Engineering 5(2): 113-133.
Stetina, Jiri, Sadao Kurohashi & Makoto Nagao. 1998. General word sense disambiguation method based on a full sentential context. Proceedings of the workshop on Usage of WordNet in Natural Language Processing, Montreal, Canada, 1-8.
Stevenson, Mark & Yorick Wilks. 2001. The interaction of knowledge sources in word sense disambiguation. Computational Linguistics, 27(3): 321-349.
Tat, Lim B., Zaharin Yusoff, Tang E. Kong & Guo C. Ming. 2001. Primitivebased word sense disambiguation for Senseval-2. Proceedings of Senseval-2: Second International Workshop on Evaluating Word Sense Disambiguation Systems, Toulouse, France, 103-106.
Vasilescu, Florentina, Philippe Langlais & Guy Lapalme. 2004. Evaluating variants of the Lesk approach for disambiguating words. Proceedings of the Conference on Language Resources and Evaluation (LREC), Lisbon, Portugal, 633-636.
Yarowsky, David. 1993. One sense per collocation. Proceedings of the ARPA Human Language Technology Workshop, Plainsboro, U.S.A., 265-271.
Yarowsky, David. 1995. Unsupervised word sense disambiguation rivaling supervised methods. Proceedings of the 33rd Annual Meeting of the Association for Computational Linguistics (ACL), Cambridge, U.S.A., 189-196.
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Mihalcea, R. (2007). Knowledge-Based Methods for WSD. In: Agirre, E., Edmonds, P. (eds) Word Sense Disambiguation. Text, Speech and Language Technology, vol 33. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-4809-8_5
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