• DocumentCode
    2733783
  • Title

    Gender Identification for Chinese E-mail documents

  • Author

    Gui-fa Teng ; Wen-Qiang Dong ; Jing Yang ; Jian-Bin Ma

  • Author_Institution
    Agric. Univ. of Hebei, Hebei
  • fYear
    2007
  • fDate
    5-7 Sept. 2007
  • Firstpage
    36
  • Lastpage
    36
  • Abstract
    In this paper, the method of gender identification for Chinese e-mail documents is described. E-mail documents´ features including linguistic features, format features and structure features were analyzed. The support vector machine algorithm was selected as classification algorithm. Experiments on a set of samples gave promising results, which proved that the method was feasible.
  • Keywords
    document handling; electronic mail; gender issues; natural languages; support vector machines; Chinese e-mail documents; format features; gender identification; linguistic features; structure features; support vector machine algorithm; Classification algorithms; Electronic mail; Information science; Machine learning algorithms; Pediatrics; Physiology; Postal services; Support vector machine classification; Support vector machines; Terminology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Innovative Computing, Information and Control, 2007. ICICIC '07. Second International Conference on
  • Conference_Location
    Kumamoto
  • Print_ISBN
    0-7695-2882-1
  • Type

    conf

  • DOI
    10.1109/ICICIC.2007.327
  • Filename
    4427682