• DocumentCode
    2210628
  • Title

    An efficient stemming for Arabic Text Classification

  • Author

    Nehar, Attia ; Ziadi, Djelloul ; Cherroun, Hadda ; Guellouma, Younes

  • Author_Institution
    Dept. d´´Inf., Z.A. Univ., Djelfa, Algeria
  • fYear
    2012
  • fDate
    18-20 March 2012
  • Firstpage
    328
  • Lastpage
    332
  • Abstract
    Using N-gram technique without stemming is not appropriate in the context of Arabic Text Classification. For this, we introduce a new stemming technique, which we call “approximate-stemming”, based on the use of Arabic patterns. These are modeled using transducers and stemming is done without depending on any dictionary. This stemmer will be used in the context of Arabic Text Classification.
  • Keywords
    natural language processing; pattern classification; text analysis; Arabic text classification; N-gram technique; approximate-stemming; transducer; Buildings; Context; Dictionaries; Educational institutions; Feature extraction; Kernel; Transducers; Arabic; Arabic Patterns; classification; kernels; transducers;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Innovations in Information Technology (IIT), 2012 International Conference on
  • Conference_Location
    Abu Dhabi
  • Print_ISBN
    978-1-4673-1100-7
  • Type

    conf

  • DOI
    10.1109/INNOVATIONS.2012.6207760
  • Filename
    6207760