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A probabilistic method for computing term‐by‐term relationships

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  • S. K. M. Wong
  • Y. Y. Yao

Abstract

This article suggests a probabilistic method to compute the term relationships from relevance information, which complements the studies on a non‐probabilistic technique called pseudo‐classification. A quadratic ranking function (i.e., a bilinear function) on the components of document and query vectors is derived by incorporating the term‐by‐term relationships. The conventional probabilistic indexing model, the probabilistic retrieval model, and our earlier generalized model are special cases of the proposed model. By exploring the different views of probability, procedures for estimating the required parameters are provided. © 1993 John Wiley & Sons, Inc.

Suggested Citation

  • S. K. M. Wong & Y. Y. Yao, 1993. "A probabilistic method for computing term‐by‐term relationships," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 44(8), pages 431-439, September.
    • Handle: RePEc:bla:jamest:v:44:y:1993:i:8:p:431-439
    DOI: 10.1002/(SICI)1097-4571(199309)44:83.0.CO;2-V
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