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A critical analysis of vector space model for information retrieval

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  • Vijay V. Raghavan
  • S. K. M. Wong

Abstract

Notations and definitions necessary to identify the concepts and relationships that are important in modelling information retrieval objects and processes in the context of vector spaces are presented. Earlier work on the use of vector model is evaluated in terms of the concepts introduced and certain problems and inconsistencies are identified. More importantly, this investigation should lead to a clear understanding of the issues and problems in using the vector space model in information retrieval. © 1986 John Wiley & Sons, Inc.

Suggested Citation

  • Vijay V. Raghavan & S. K. M. Wong, 1986. "A critical analysis of vector space model for information retrieval," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 37(5), pages 279-287, September.
    • Handle: RePEc:bla:jamest:v:37:y:1986:i:5:p:279-287
    DOI: 10.1002/(SICI)1097-4571(198609)37:53.0.CO;2-Q
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    Cited by:

    1. Alexandros Garefalakis & Nikolaos Sariannidis & Christos Lemonakis, 2020. "Narrative disclosure guidelines for CARs: an operational-based tool," Annals of Operations Research, Springer, vol. 294(1), pages 107-122, November.
    2. Pei-Chun Lee & Hsin-Ning Su & Te-Yi Chan, 2010. "Assessment of ontology-based knowledge network formation by Vector-Space Model," Scientometrics, Springer;Akadémiai Kiadó, vol. 85(3), pages 689-703, December.
    3. Zhixiang Chen & Bin Fu & John Abraham, 2010. "A quadratic lower bound for Rocchio’s similarity-based relevance feedback algorithm with a fixed query updating factor," Journal of Combinatorial Optimization, Springer, vol. 19(2), pages 134-157, February.
    4. Nenad Tomašev, 2017. "Extracting the patterns of truthfulness from political information systems in Serbia," Information Systems Frontiers, Springer, vol. 19(1), pages 109-127, February.

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