Co-clustering with recursive elimination for verb synonym extraction from large text corpus

Koichi Takeuchi, Hideyuki Takahashi

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

The extraction of verb synonyms is a key technology to build a verb dictionary as a language resource. This paper presents a coclustering-based verb synonym extraction approach that increases the number of extracted meanings of polysemous verbs from a large text corpus. For verb synonym extraction with a clustering approach dealing with polysemous verbs can be one problem issue because each polysemous verb should be categorized into different clusters depending on each meaning; thus there is a high possibility of failing to extract some of the meanings of polysemous verbs. Our proposed approach can extract the different meanings of polysemous verbs by recursively eliminating the extracted clusters from the initial data set. The experimental results of verb synonym extraction show that the proposed approach increases the correct verb clusters by about 50% with a 0.9% increase in precision and a 1.5% increase in recall over the previous approach.

Original languageEnglish
Pages (from-to)2334-2340
Number of pages7
JournalIEICE Transactions on Information and Systems
VolumeE92-D
Issue number12
DOIs
Publication statusPublished - 2009

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Glossaries

Keywords

  • Co-clustering
  • Polysemy
  • Recursive elimination
  • Verb synonyms

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Software
  • Artificial Intelligence
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition

Cite this

Co-clustering with recursive elimination for verb synonym extraction from large text corpus. / Takeuchi, Koichi; Takahashi, Hideyuki.

In: IEICE Transactions on Information and Systems, Vol. E92-D, No. 12, 2009, p. 2334-2340.

Research output: Contribution to journalArticle

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