• DocumentCode
    2387872
  • Title

    Identifying citing sentences in research papers using supervised learning

  • Author

    Sugiyama, Kazunari ; Kumar, Tarun ; Kan, Min-Yen ; Tripathi, Ramesh C.

  • Author_Institution
    Dept. of Comput. Sci., Nat. Univ. of Singapore, Singapore, Singapore
  • fYear
    2010
  • fDate
    17-18 March 2010
  • Firstpage
    67
  • Lastpage
    72
  • Abstract
    Researchers have largely focused on analyzing citation links from one scholarly work to another. Such citing sentences are an important part of the narrative in a research article. If we can automatically identify such sentences, we can devise an editor that helps suggest when a particular piece of text needs to be backed up with a citation or not. In this paper, we propose a method for identifying citing sentences by constructing a classifier using supervised learning. Our experiments show that simple language features such as proper nouns and the labels of previous and next sentences are effective features to identifying citing sentences.
  • Keywords
    citation analysis; learning (artificial intelligence); pattern classification; citing sentences identification; pattern classifier; research paper; supervised learning; Bibliographies; Citation analysis; Computer science; Information analysis; Information retrieval; Information technology; Intersymbol interference; Natural languages; Software libraries; Supervised learning; citation analysis; digital library; discourse processing; information retrieval;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Retrieval & Knowledge Management, (CAMP), 2010 International Conference on
  • Conference_Location
    Shah Alam, Selangor
  • Print_ISBN
    978-1-4244-5650-5
  • Type

    conf

  • DOI
    10.1109/INFRKM.2010.5466945
  • Filename
    5466945