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

Koichi Takeuchi, Hideyuki Takahashi


2 被引用数 (Scopus)


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.

ジャーナルIEICE Transactions on Information and Systems
出版ステータスPublished - 2009

ASJC Scopus subject areas

  • ソフトウェア
  • ハードウェアとアーキテクチャ
  • コンピュータ ビジョンおよびパターン認識
  • 電子工学および電気工学
  • 人工知能


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