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Highlights: Language‐ and domain‐independent automatic indexing terms for abstracting

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  • Jonathan D. Cohen

Abstract

A method of drawing index terms from text is presented. The approach uses no stop list, stemmer, or other language‐ and domain‐specific component, allowing operation in any language or domain with only trivial modification. The method uses n‐gram counts, achieving a function similar to, but more general than, a stemmer. The generated index terms, which the author calls “highlights,” are suitable for identifying the topic for perusal and selection. An extension is also described and demonstrated which selects index terms to represent a subset of documents, distinguishing them from the corpus. Some experimental results are presented, showing operation in English, Spanish, German, Georgian, Russian, and Japanese. © 1995 John Wiley & Sons, Inc.

Suggested Citation

  • Jonathan D. Cohen, 1995. "Highlights: Language‐ and domain‐independent automatic indexing terms for abstracting," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 46(3), pages 162-174, April.
  • Handle: RePEc:bla:jamest:v:46:y:1995:i:3:p:162-174
    DOI: 10.1002/(SICI)1097-4571(199504)46:33.0.CO;2-6
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    Cited by:

    1. Leo Egghe, 2000. "The Distribution of N-Grams," Scientometrics, Springer;Akadémiai Kiadó, vol. 47(2), pages 237-252, February.
    2. Mehmet Ali Abdulhayoglu & Bart Thijs & Wouter Jeuris, 2016. "Using character n-grams to match a list of publications to references in bibliographic databases," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(3), pages 1525-1546, December.

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