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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/257

Title: Word Sense Disambiguation
Authors: SALINI, M T
Keywords: Word Sense Disambiguation
Word Sense Discrimination
Context
Lexical ambiguity
Knowlege source
Sense Inventory
Sense annotation
Issue Date: 14-Jun-2010
Abstract: Words have different meanings based on the context of the word usage in a sentence. Word sense is one of the meanings of a word. Human language is ambiguous, so that many words can be interpreted in multiple ways depending on the context in which they occur. 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. WSD can be viewed as a classification task: word senses are the classes, and an automatic classification method is used to assign each occurrence of a word to one or more classes based on the evidence from the context and from external knowledge sources. WSD heavily relies on knowledge. Knowledge sources provide data which are essential to associate senses with words. 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. Here, some of the knowledge sources used in WSD, different approaches for WSD (supervised, unsupervised and Knowledge-based ) and evaluation of WSD systems are discussed. The applications of WSD are also seen.
URI: http://hdl.handle.net/123456789/257
Appears in Collections:MTech 2009-2011 Batch

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