Word sense induction using independent component analysis

Petr Šimon, Jia Fei Hong

Research output: Contribution to conferencePaper

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 Dec 1
Externally publishedYes
Event19th Conference on Computational Linguistics and Speech Processing, ROCLING 2007 - Taipei, Taiwan
Duration: 2007 Sep 62007 Sep 7

Other

Other19th Conference on Computational Linguistics and Speech Processing, ROCLING 2007
CountryTaiwan
CityTaipei
Period07/9/607/9/7

ASJC Scopus subject areas

  • Language and Linguistics
  • Speech and Hearing

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  • Cite this

    Šimon, P., & Hong, J. F. (2007). Word sense induction using independent component analysis. Paper presented at 19th Conference on Computational Linguistics and Speech Processing, ROCLING 2007, Taipei, Taiwan.