Automatic retrieval and clustering of similar words

  • Authors:
  • Dekang Lin

  • Affiliations:
  • University of Manitoba, Winnipeg, Manitoba, Canada

  • Venue:
  • COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
  • Year:
  • 1998

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Abstract

Bootstrapping semantics from text is one of the greatest challenges in natural language learning. We first define a word similarity measure based on the distributional pattern of words. The similarity measure allows us to construct a thesaurus using a parsed corpus. We then present a new evaluation methodology for the automatically constructed thesaurus. The evaluation results show that the thesaurus is significantly closer to WordNet than Roget Thesaurus is.