Word Sense Disambiguation by Machine Learning Approach: A Short Survey

Authors:
Doina Tatar
Affiliations:
Faculty of Mathematics and Computer Science, University Babeş-Bolyai, Str. Kogalniceanu nr.1, Cluj-Napoca, Romania. dtatar@cs.ubbcluj.ro (Corresp.)
Venue:
Fundamenta Informaticae - Contagious Creativity - In Honor of the 80th Birthday of Professor Solomon Marcus
Year:
2004

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Abstract

There is a renewed interest in word sense disambiguation (WSD) as it contributes to various applications in natural language processing. In this paper we survey vector-based methods for WSD in machine learning. All the methods are corpus-based and use definition of context in the sense introduced by S. Marcus [11].