Word sense disambiguation with semantic networks

George Tsatsaronis, Iraklis Varlamis, Michalis Vazirgiannis

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

13 Scopus citations

Abstract

Word sense disambiguation (WSD) methods evolve towards exploring all of the available semantic information that word thesauri provide. In this scope, the use of semantic graphs and new measures of semantic relatedness may offer better WSD solutions. In this paper we propose a new measure of semantic relatedness between any pair of terms for the English language, using WordNet as our knowledge base. Furthermore, we introduce a new WSD method based on the proposed measure. Experimental evaluation of the proposed method in benchmark data shows that our method matches or surpasses state of the art results. Moreover, we evaluate the proposed measure of semantic relatedness in pairs of terms ranked by human subjects. Results reveal that our measure of semantic relatedness produces a ranking that is more similar to the human generated one, compared to rankings generated by other related measures of semantic relatedness proposed in the past.

Original languageEnglish
Title of host publicationText, Speech and Dialogue - 11th International Conference, TSD 2008, Proceedings
Pages219-226
Number of pages8
DOIs
StatePublished - 2008
Externally publishedYes
Event11th International Conference on Text, Speech and Dialogue, TSD 2008 - Brno, Czech Republic
Duration: Sep 8 2008Sep 12 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5246 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference11th International Conference on Text, Speech and Dialogue, TSD 2008
Country/TerritoryCzech Republic
CityBrno
Period09/8/0809/12/08

Keywords

  • Semantic networks
  • Word sense disambiguation
  • WordNet

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