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2018 | OriginalPaper | Chapter

WordNet and Wiktionary-Based Approach for Word Sense Disambiguation

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

Published in: Transactions on Computational Collective Intelligence XXIX

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 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 W3SD (This paper is an extended version of our work [4] published in the 8^th International Conference on Computational Collective Intelligence.) 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 WordNet and Wiktionary features through the taxonomic information content from WordNet and the glosses from Wiktionary. 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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Title: WordNet and Wiktionary-Based Approach for Word Sense Disambiguation
Authors: Mohamed Ben Aouicha
Mohamed Ali Hadj Taieb
Hania Ibn Marai
Publisher: Springer International Publishing
Book: Transactions on Computational Collective Intelligence XXIX
Print ISBN: 978-3-319-90286-9

Electronic ISBN: 978-3-319-90287-6

Copyright Year: 2018
DOI: https://doi.org/10.1007/978-3-319-90287-6_7

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