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A study of topic similarity measures

Published:25 July 2004Publication History

ABSTRACT

In this poster we describe an investigation of topic similarity measures. We elicit assessments on the similarity of 10 pairs of topic from 76 subjects and use these as a benchmark to assess how well each measure performs. The measures have the potential to form the basis of a predictive technique, for adaptive search systems. The results of our evaluation show that measures based on the level of correlation between topics concords most with general subject perceptions of search topic similarity.

References

  1. Harman, D. (1986) 'An Experimental Study of the Factors Important in Document Ranking'. Proceedings of the 9th ACM SIGIR Conference, 186--193. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Lee, L. (1999) 'Measures of Distributional Similarity'. Proceedings of the 37th Annual Meeting of the Association for Computational Linguistics, 25--32. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Maes, P. (1994) 'Agents that Reduce Work and Information Overload'. Communications of the ACM, 37(7), 30--40. Google ScholarGoogle ScholarDigital LibraryDigital Library

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  1. A study of topic similarity measures

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    • Published in

      cover image ACM Conferences
      SIGIR '04: Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
      July 2004
      624 pages
      ISBN:1581138814
      DOI:10.1145/1008992

      Copyright © 2004 ACM

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 25 July 2004

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      Overall Acceptance Rate792of3,983submissions,20%

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