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The limitations of term co‐occurrence data for query expansion in document retrieval systems

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  • Helen J. Peat
  • Peter Willett

Abstract

Term cooccurrence data has been extensively used in document retrieval systems for the identification of indexing terms that are similar to those that have been specified in a user query: these similar terms can then be used to augment the original query statement. Despite the plausibility of this approach to query expansion, the retrieval effectiveness of the expanded queries is often no greater than, or even less than, the effectiveness of the unexpanded queries. This article demonstrates that the similar terms identified by cooccurrence data in a query expansion system tend to occur very frequently in the database that is being searched. Unfortunately, frequent terms tend to discriminate poorly between relevant and nonrelevant documents, and the general effect of query expansion is thus to add terms that do little or nothing to improve the discriminatory power of the original query. © 1991 John Wiley & Sons, Inc.

Suggested Citation

  • Helen J. Peat & Peter Willett, 1991. "The limitations of term co‐occurrence data for query expansion in document retrieval systems," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 42(5), pages 378-383, June.
    • Handle: RePEc:bla:jamest:v:42:y:1991:i:5:p:378-383
    DOI: 10.1002/(SICI)1097-4571(199106)42:53.0.CO;2-8
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    Cited by:

    1. Dietmar Wolfram, 2015. "The symbiotic relationship between information retrieval and informetrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(3), pages 2201-2214, March.
    2. Xicheng Yin & Hongwei Wang & Pei Yin & Hengmin Zhu & Zhenyu Zhang, 2020. "A co-occurrence based approach of automatic keyword expansion using mass diffusion," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(3), pages 1885-1905, September.
    3. Zhang, Yi & Shang, Lining & Huang, Lu & Porter, Alan L. & Zhang, Guangquan & Lu, Jie & Zhu, Donghua, 2016. "A hybrid similarity measure method for patent portfolio analysis," Journal of Informetrics, Elsevier, vol. 10(4), pages 1108-1130.
    4. Shuqing Li & Ying Sun & Dagobert Soergel, 2015. "A new method for automatically constructing domain-oriented term taxonomy based on weighted word co-occurrence analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(3), pages 1023-1042, June.
    5. Wylie, Peter J., 1995. "Partial equilibrium estimates of manufacturing trade creation and diversion due to NAFTA," The North American Journal of Economics and Finance, Elsevier, vol. 6(1), pages 65-84.
    6. Veda C. Storey & Andrew Burton-Jones & Vijayan Sugumaran & Sandeep Purao, 2008. "CONQUER: A Methodology for Context-Aware Query Processing on the World Wide Web," Information Systems Research, INFORMS, vol. 19(1), pages 3-25, March.

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