Word sense disambiguation
ACM Computing SurveysPublished 1 February 2009
Roberto Navigli
Citations1,814
SJR quartileQ1
SJR score5.80
SNIP11.03
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TL;DR
This work introduces the reader to the motivations for solving the ambiguity of words and provides a description of the task, and overviews supervised, unsupervised, and knowledge-based approaches.
Abstract
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 difficult problems in artificial 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.
Keywords
Computer Science
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