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Clumping properties of content‐bearing words

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  • A. Bookstein
  • S. T. Klein
  • T. Raita

Abstract

Information Retrieval Systems identify content bearing words, and possibly also assign weights, as part of the process of formulating requests. For optimal retrieval efficiency, it is desirable that this be done automatically. This article defines the notion of serial clustering of words in text, and explores the value of such clustering as an indicator of a word's bearing content. This approach is flexible in the sense that it is sensitive to context: a term may be assessed as content‐bearing within one collection, but not another. Our approach, being numerical, may also be of value in assigning weights to terms in requests. Experimental support is obtained from natural text databases in three different languages. © 1998 John Wiley & Sons, Inc.

Suggested Citation

  • A. Bookstein & S. T. Klein & T. Raita, 1998. "Clumping properties of content‐bearing words," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 49(2), pages 102-114, February.
    • Handle: RePEc:bla:jamest:v:49:y:1998:i:2:p:102-114
    DOI: 10.1002/(SICI)1097-4571(199802)49:23.0.CO;2-5
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    1. Zhou, Xiao & Huang, Lu & Porter, Alan & Vicente-Gomila, Jose M., 2019. "Tracing the system transformations and innovation pathways of an emerging technology: Solid lipid nanoparticles," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 785-794.

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