Word sense induction using independent component analysis

Petr Šimon, Jia Fei Hong

Research output: Contribution to conferencePaperpeer-review

Abstract

This paper explores the possibilities of using independent component analysis (ICA) for features extraction that could be applied to word sense induction. Two different methods for using the features derived by ICA are introduced and results evaluated. Our goal in this paper is to observe whether ICA based feature vectors can be efficiently used for word context encoding and subsequently for clustering. We show that it is possible, further research is, however, necessary to ascertain more reliable results.

Original languageEnglish
Publication statusPublished - 2007
Externally publishedYes
Event19th Conference on Computational Linguistics and Speech Processing, ROCLING 2007 - Taipei, Taiwan
Duration: 2007 Sept 62007 Sept 7

Other

Other19th Conference on Computational Linguistics and Speech Processing, ROCLING 2007
Country/TerritoryTaiwan
CityTaipei
Period2007/09/062007/09/07

ASJC Scopus subject areas

  • Speech and Hearing
  • Language and Linguistics

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