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A study of topic similarity measures

Published: 25 July 2004 Publication 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.
[2]
Lee, L. (1999) 'Measures of Distributional Similarity'. Proceedings of the 37th Annual Meeting of the Association for Computational Linguistics, 25--32.
[3]
Maes, P. (1994) 'Agents that Reduce Work and Information Overload'. Communications of the ACM, 37(7), 30--40.

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    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
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 25 July 2004

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