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date: 24 June 2019

Abstract and Keywords

Word sense disambiguation (WSD) is the process of identifying the meanings of words in context. The difficulty of this problem stems from the subtlety of word sense differences and the need for some level of understanding. This chapter describes the main approaches to the problem, methods for evaluating performance, and potential applications. Recent developments in deep learning have led to renewed interest in this long-established task.

Keywords: word sense disambiguation, natural-language understanding, lexical semantics, knowledge-based, supervised learning, unsupervised learning

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