Word Sense Disambiguation: A Survey ROBERTO NAVIGLI Universita di Roma La Sapienza ` Word sense disambiguation (WSD) is the ability to identify the meaning of words in context in a computational manner. WSD is considered an AI-complete problem, that is, a task whose solution is at least as hard as the most dif cult problems in arti cial intelligence. We introduce the reader to the motivations for solving the ambiguity of words and provide a description of the task. We overview supervised, unsupervised, and knowledge-based approaches. The assessment of WSD systems is discussed in the context of the Senseval/Semeval campaigns, aiming at the objective evaluation of systems participating in several different disambiguation tasks. Finally, applications, open problems, and future directions are discussed. Categories and Subject Descriptors: I.2.7 [Arti cial Intelligence]: Natural Language Processing Text analysis; I.2.4 [Arti cial Intelligence]: Knowledge Representation Formalisms and Methods General Terms: Algorithms, Experimentation, Measurement, Performance Additional Key Words and Phrases: Word sense disambiguation, word sense discrimination, WSD, lexical semantics, lexical ambiguity, sense annotation, semantic annotation ACM Reference Format: Navigli, R. 2009. Word sense disambiguation: A survey. ACM Comput. Surv. 41, 2, Article 10 (February 2009), 69 pages DOI = 10.1145/1459352.1459355 http://doi.acm.org/10.1145/1459352.1459355 1. INTRODUCTION
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Word sense disambiguation: A survey
Navigli, Roberto
Follow ACM Computing Surveys (CSUR)
, Volume 41 (2)
Association for Computing Machinery – Feb 1, 2009
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