• DocumentCode
    2909991
  • Title

    Authorship Attribution in Arabic using a hybrid of evolutionary search and linear discriminant analysis

  • Author

    Shaker, Kareem ; Corne, David

  • Author_Institution
    Sch. of Math. & Comput. Sci., Heriot-Watt Univ., Edinburgh, UK
  • fYear
    2010
  • fDate
    8-10 Sept. 2010
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Authorship Attribution is the problem of determining the authorship of one or more texts. Applications include disputed authorship, or deciding which of a collection of pieces of text were by the same author. A popular and successful approach is to characterize a specific author in terms of the usage pattern of function words. These are common words that are unrelated to subject matter, and tend to be used in specific ways by different authors. In English, a well-known collection of 70 function words is often used for this purpose. Previously, using a hybrid of evolutionary search and linear-discriminant analysis (LDA), we have shown excellent performance in authorship attribution in English based on a function word approach. Here, for the first time, we propose and test a set of Arabic function words for use in Arabic authorship attribution. Tests indicate that the chosen collection forms an effective basis for authorship attribution in Arabic.
  • Keywords
    evolutionary computation; text analysis; Arabic authorship attribution; Arabic function word approach; evolutionary search; linear discriminant analysis; usage pattern; Accuracy; Biological cells; Books; Learning systems; Linear discriminant analysis; Support vector machine classification; Training;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence (UKCI), 2010 UK Workshop on
  • Conference_Location
    Colchester
  • Print_ISBN
    978-1-4244-8774-5
  • Electronic_ISBN
    978-1-4244-8773-8
  • Type

    conf

  • DOI
    10.1109/UKCI.2010.5625580
  • Filename
    5625580