Genetic Word Sense Disambiguation Algorithm

  • Authors:

  • Chunhui Zhang;Yiming Zhou;Trevor Martin

  • Affiliations:

  • -;-;-

  • Venue:
  • IITA '08 Proceedings of the 2008 Second International Symposium on Intelligent Information Technology Application - Volume 01
  • Year:
  • 2008

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Abstract

A novel unsupervised genetic word sense disambiguation (GWSD) algorithm is proposed in this paper. The algorithm first uses WordNet to determine all possible senses for a set of words, then a genetic algorithm is used to maximize the overall semantic similarity on this set of words. A novel conceptual similarity function combining domain information is also proposed to compute similarity between senses in WordNet. GWSD is tested on two sets of domain terms and obtains good results. A weighted genetic word sense disambiguation (WGWSD) algorithm is then proposed to disambiguate words in a general corpus. Experiments on SemCor are carried out to compare WGWSD with previous work.