한국컴퓨터정보학회논문지 (Journal of the Korea Society of Computer and Information)

  • 제22권9호
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  • Pages.17-24
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  • 2017
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  • 1598-849X(pISSN)
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  • 2383-9945(eISSN)
한국컴퓨터정보학회 (Korean Society of Computer Information)
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A Term Importance-based Approach to Identifying Core Citations in Computational Linguistics Articles

  • Kang, In-Su (Dept. of Computer Science & Engineering, Kyungsung University)
  • 투고 : 2017.05.31
  • 심사 : 2017.09.04
  • 발행 : 2017.09.30
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초록

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.

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참고문헌

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