• DocumentCode
    2026634
  • Title

    Claper: Recommend classical papers to beginners

  • Author

    Wang, Yonggang ; Zhai, Ennan ; Hu, Jianbin ; Chen, Zhong

  • Author_Institution
    Sch. of Electron. Eng. & Comput. Sci., Peking Univ., Beijing, China
  • Volume
    6
  • fYear
    2010
  • fDate
    10-12 Aug. 2010
  • Firstpage
    2777
  • Lastpage
    2781
  • Abstract
    Classical papers are of great help for beginners to get familiar with a new research area. However, digging them out is a difficult problem. This paper proposes Claper, a novel academic recommendation system based on two proven principles: the Principle of Download Persistence and the Principle of Citation Approaching (we prove them based on real-world datasets). The principle of download persistence indicates that classical papers have few decreasing download frequencies since they were published. The principle of citation approaching indicates that a paper which cites a classical paper is likely to cite citations of that classical paper. Our experimental results based on large-scale real-world datasets illustrate Claper can effectively recommend classical papers of high quality to beginners and thus help them enter their research areas.
  • Keywords
    citation analysis; recommender systems; Claper recommendation system; academic recommendation system; citation approaching principle; classical papers; download persistence principle; Computer science; Educational institutions; Electronic mail; Libraries; Measurement; Peer to peer computing; Training;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems and Knowledge Discovery (FSKD), 2010 Seventh International Conference on
  • Conference_Location
    Yantai, Shandong
  • Print_ISBN
    978-1-4244-5931-5
  • Type

    conf

  • DOI
    10.1109/FSKD.2010.5569227
  • Filename
    5569227