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2016 | OriginalPaper | Chapter

WSD-TIC: Word Sense Disambiguation Using Taxonomic Information Content

Authors : Mohamed Ben Aouicha, Mohamed Ali Hadj Taieb, Hania Ibn Marai

Published in: Computational Collective Intelligence

Publisher: Springer International Publishing

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Abstract

Word sense disambiguation (WSD) is the ability to identify the meaning of words in context in a computational manner. WSD is considered as an AI-complete problem, that is, a task whose solution is at least as hard as the most difficult problems in artificial intelligence. This is basically used in application like information retrieval, machine translation, information extraction because of its semantics understanding. This paper describes the proposed approach (WSD-TIC) which is based on the words surrounding the polysemous word in a context. Each meaning of these words is represented by a vector composed of weighted nouns using taxonomic information content. The main emphasis of this paper is feature selection for disambiguation purpose. The assessment of WSD systems is discussed in the context of the Senseval campaign, aiming at the objective evaluation of our proposal to the systems participating in several different disambiguation tasks.

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Footnotes
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Metadata
Title
WSD-TIC: Word Sense Disambiguation Using Taxonomic Information Content
Authors
Mohamed Ben Aouicha
Mohamed Ali Hadj Taieb
Hania Ibn Marai
Copyright Year
2016
Book
Computational Collective Intelligence

Print ISBN: 978-3-319-45242-5

Electronic ISBN: 978-3-319-45243-2

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-45243-2_12

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