• DocumentCode
    2397311
  • Title

    Wikipedia edit number prediction from the past edit record based on auto-supervised learning

  • Author

    Yoshida, Yutaka ; Ohwada, Hayato

  • Author_Institution
    Dept. of Ind. Adm., Tokyo Univ. of Sci., Tokyo, Japan
  • fYear
    2012
  • fDate
    19-20 May 2012
  • Firstpage
    2415
  • Lastpage
    2419
  • Abstract
    This paper describes our approach to the Wikipedia Participation Challenge that seeks to predict the number of edits a Wikipedia editor will make in the next five months. Our approach takes a time series analysis approach in combination with supervised learning, which we call auto-supervised learning. The best model of our solutions achieved a 41% improvement over WMF´s baseline predictive model. The result is low accuracy compared with related work but showed 9th place in ICDM contest.
  • Keywords
    Web sites; learning (artificial intelligence); time series; ICDM contest; Wikipedia edit number prediction; Wikipedia editor; Wikipedia participation challenge; auto-supervised learning; past edit record; time series analysis approach; Electronic publishing; Encyclopedias; Internet; Radio frequency; Reliability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems and Informatics (ICSAI), 2012 International Conference on
  • Conference_Location
    Yantai
  • Print_ISBN
    978-1-4673-0198-5
  • Type

    conf

  • DOI
    10.1109/ICSAI.2012.6223541
  • Filename
    6223541