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A probabilistic approach to automatic keyword indexing. Part II. An algorithm for probabilistic indexing

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  • Stephen P. Harter

Abstract

In Part I of this study,* a mixture of two Poisson distributions was examined as a model of specialty word distribution. Formulas expressing the three parameters of the model in terms of empirical frequency statistics were derived, and a statistical measure intended to identify specialty words, consistent with the model, was proposed. In the present paper, Part II of the study, a probabilistic model of keyword indexing is outlined, and some of the consequences of the model are examined. An algorithm defining a measure of indexability is developed‐a measure intended to reflect the relative significance of words in documents. The measure is evaluated and is found to consistently produce indexes superior to those produced by another measure which had previously been identified in the literature as producing the best results.

Suggested Citation

  • Stephen P. Harter, 1975. "A probabilistic approach to automatic keyword indexing. Part II. An algorithm for probabilistic indexing," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 26(5), pages 280-289, September.
    • Handle: RePEc:bla:jamest:v:26:y:1975:i:5:p:280-289
    DOI: 10.1002/asi.4630260504
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    Cited by:

    1. Hoppenbrouwers, J.J.A.C. & Paijmans, J.J., 2000. "Invading the fortress : How to beseige reinforced information bunkers," Other publications TiSEM 62e33d30-6377-48c8-9bdf-b, Tilburg University, School of Economics and Management.

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