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A probabilistic approach to automatic keyword indexing. Part I. On the Distribution of Specialty Words in a Technical Literature

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  • Stephen P. Harter

Abstract

The problem studied in this research is that of developing a set of formal statistical rules for the purpose of identifying the keywords of a document‐words likely to be useful as index terms for that document. The research was prompted by the observation, made by a number of writers, that non‐specialty words, words which possess little value for indexing purposes, tend to be distributed at random in a collection of documents. In contrast, specialty words are not so distributed. In Part I of the study, a mixture of two Poisson distributions is examined in detail as a model of specialty word distribution, and formulas expressing the three parameters of the model in terms of empirical frequency statistics are derived. The fit of the model is tested on an experimental document collection and found to be acceptable for the purposes of the study. A measure intended to identify specialty words, consistent with the 2‐Poisson model, is proposed and evaluated.

Suggested Citation

  • Stephen P. Harter, 1975. "A probabilistic approach to automatic keyword indexing. Part I. On the Distribution of Specialty Words in a Technical Literature," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 26(4), pages 197-206, July.
    • Handle: RePEc:bla:jamest:v:26:y:1975:i:4:p:197-206
    DOI: 10.1002/asi.4630260402
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    Cited by:

    1. Marcelo A Montemurro & Damián H Zanette, 2013. "Keywords and Co-Occurrence Patterns in the Voynich Manuscript: An Information-Theoretic Analysis," PLOS ONE, Public Library of Science, vol. 8(6), pages 1-9, June.

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