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A Study on Keyword Extraction From a Single Document Using Term Clustering

  • Journal of the Korean Society for Library and Information Science
  • 2010, 44(3), pp.155-173
  • DOI : 10.4275/KSLIS.2010.44.3.155
  • Publisher : 한국문헌정보학회
  • Research Area : Interdisciplinary Studies > Library and Information Science
  • Received : July 19, 2010
  • Accepted : August 11, 2010

Han, Seung Hee 1

1서울여자대학교

Accredited

ABSTRACT

In this study, a new keyword extraction algorithm is applied to a single document with term clustering. A single document is divided by multiple passages, and two ways of calculating similarities between two terms are investigated; the first-order similarity and the second-order distributional similarity. In this experiment, the best cluster performance is achieved with a 50-term passage from the second-order distributional similarity. From the results of first experiment, the second-order distribution similarity was also applied to various keyword extraction methods using statistic information of terms. In the second experiment, (paragraph frequency) and (term frequency by inverse paragraph frequency) were found to improve the overall performance of keyword extraction. Therefore, it showed that the algorithm fulfills the necessary conditions which good keywords should have.

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