Word sense disambiguation in information retrieval revisited

  • Authors:
  • Christopher Stokoe;Michael P. Oakes;John Tait

  • Affiliations:
  • The University of Sunderland, St Peters Way, UK;The University of Sunderland, St Peters Way, UK;The University of Sunderland, St Peters Way, UK

  • Venue:
  • Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
  • Year:
  • 2003

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Abstract

Word sense ambiguity is recognized as having a detrimental effect on the precision of information retrieval systems in general and web search systems in particular, due to the sparse nature of the queries involved. Despite continued research into the application of automated word sense disambiguation, the question remains as to whether less than 90% accurate automated word sense disambiguation can lead to improvements in retrieval effectiveness. In this study we explore the development and subsequent evaluation of a statistical word sense disambiguation system which demonstrates increased precision from a sense based vector space retrieval model over traditional TF*IDF techniques.