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Automatic text analysis based on transition phenomena of word occurrences

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  • Miranda Lee Pao

Abstract

A method of selecting index terms directly from a word frequency list is described. The original idea was suggested by Goffman who reasoned that the most content‐bearing words of a given text would occur at the transition region at which Zipf's First Law of words of high frequency of occurrences begins to take on properties of words of low frequency of occurrences. Word frequencies of two articles were analyzed. Results seem to indicate that the automated selection of index terms from a frequency list holds some promise for automatic indexing.

Suggested Citation

  • Miranda Lee Pao, 1978. "Automatic text analysis based on transition phenomena of word occurrences," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 29(3), pages 121-124, May.
    • Handle: RePEc:bla:jamest:v:29:y:1978:i:3:p:121-124
    DOI: 10.1002/asi.4630290303
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    Cited by:

    1. Eduardo C. Oliveira & Michele N. Juca, 2021. "Multinational Dividend Policies: A Systematic Literature Review to Future," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(1), pages 442-465.

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