Definition
Ambiguity is inherent to human language. In particular, word sense ambiguity is prevalent in all natural languages, with a large number of the words in any given language carrying more than one meaning. For instance, the English noun plant can mean green plant or factory; similarly the French word feuille can mean leaf or paper. The correct sense of an ambiguous word can be selected based on the context where it occurs, and correspondingly the problem of word sense disambiguation is defined as the task of automatically assigning the most appropriate meaning to a polysemous word within a given context.
Motivation and Background
Word sense disambiguation is considered one of the most difficult problems in natural language processing, due to the high semantic ambiguity that is typically associated with language. It was first noted as a problem in the context of machine translation, when Warren Weaver, in his famous 1949...
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Recommended Reading
Agirre E, Edmonds P (2006) Word sense disambiguation: algorithms and applications. Springer, Berlin. http://www.wsdbook.org
Chklovski T, Mihalcea R (2002) Building a sense tagged corpus with open mind word expert. In: Proceedings of ACL 2002 workshop on WSD, Philadelphia
Leacock C, Chodorow M, Miller GA (1998) Using corpus statistics and wordnet relations for sense identification. Comput Linguist 24(1):147–165
Lee YK, Ng HT (2002) An empirical evaluation of knowledge sources and learning algorithms for word sense disambiguation. In: Proceedings of EMNLP 2002, Philadelphia
Lesk M (1986) Automatic sense disambiguation using machine readable dictionaries: how to tell a pine cone from an ice cream cone. In: SIGDOC 1986, Toronto
Mihalcea R (1999) An automatic method for generating sense tagged corpora. In: Proceedings of AAAI 1999, Orlando
Mihalcea R (2002) Bootstrapping large sense tagged corpora. In: Proceedings of LREC 2002, Las Palmas
Mihalcea R (2007) Using wikipedia for automatic word sense disambiguation. In: Proceedings of NAACL 2007, Rochester
Mihalcea R, Pedersen T (2005) Advances in word sense disambiguation. Tutorial presented at IBERAMIA 2004, ACL 2005, AAAI 2005. http://www.d.umn.edu/~tpederse/WSDTutorial.html
Mooney R (1996) Comparative experiments on disambiguating word senses: an illustration of the role of bias in machine learning. In: Proceedings of EMNLP, Philadelphia
Ng HT, Lee HB (1996) Integrating multiple knowledge sources to disambiguate word sense: an examplar-based approach. In: Proceedings of ACL, Santa Cruz
Ng HT, Wang B, Chan YS (2003) Exploiting parallel texts for word sense disambiguation: an empirical study. In: Proceedings of ACL, Sapporo
Pedersen T (1998) Learning probabilistic models of word sense disambiguation. Ph.D. dissertation. Southern Methodist University
Schutze H (1998) Automatic word sense discrimination. Comput Linguist 24(1):97–123
Weaver W (1995) Translation. In: Locke WN, Booth AD (eds) Machine translation of languages: fourteen essays. MIT Press, Cambridge, MA
Yarowsky D (1995) Unsupervised word sense disambiguation rivaling supervised methods. In: Proceedings of ACL, Cambridge, MA
Yarowsky D (2000) Hierarchical decision lists for word sense disambiguation. Comput Hum 34(1–2): 179–186
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Mihalcea, R. (2017). Word Sense Disambiguation. In: Sammut, C., Webb, G.I. (eds) Encyclopedia of Machine Learning and Data Mining. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7687-1_882
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