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A Term Importance-based Approach to Identifying Core Citations in Computational Linguistics Articles

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2017, 22(9), pp.17-24
  • DOI : 10.9708/jksci.2017.22.09.017
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science
  • Received : May 31, 2017
  • Accepted : September 4, 2017
  • Published : September 29, 2017

In-Su Kang 1

1경성대학교

Accredited

ABSTRACT

Core citation recognition is to identify influential ones among the prior articles that a scholarly article cite. Previous approaches have employed citing-text occurrence information, textual similarities between citing and cited article, etc. This study proposes a term-based approach to core citation recognition, which exploits the importance of individual terms appearing in in-text citation to calculate influence-strength for each cited article. Term importance is computed using various frequency information such as term frequency(tf) in in-text citation, tf in the citing article, inverse sentence frequency in the citing article, inverse document frequency in a collection of articles. Experiments using a previous test set consisting of computational linguistics articles show that the term-based approach performs comparably with the previous approaches. The proposed technique could be easily extended by employing other term units such as n-grams and phrases, or by using new term-importance formulae.

Citation status

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This paper was written with support from the National Research Foundation of Korea.