• DocumentCode
    1930802
  • Title

    Automatic extraction of Arabic multi-word terms

  • Author

    Al Khatib, K. ; Badarneh, Amer

  • Author_Institution
    Dept. of Comput. Sci., Jordan Univ. of Sci. & Technol., Irbid, Jordan
  • fYear
    2010
  • fDate
    18-20 Oct. 2010
  • Firstpage
    411
  • Lastpage
    418
  • Abstract
    Whereas a wide range of methods has been conducted to English multi-word terms (MWTs) extraction, relatively few studied have been applied to Arabic MWTs extraction. In this paper, we present an efficient approach for automatic extraction of Arabic MWTs. The approach relies on two main filtering steps: the linguistic filter, where simple part of speech (POS) tagger is used to extract candidate MWTs matching given syntactic patterns, and the statistical filter, where two statistical methods (log-likelihood ratio and C-value) are used to rank candidate MWTs. Many types of variations (e.g. inflectional variants) are taken into consideration to improve the quality of extracted MWTs. We obtained promising results in both coverage and precision of MWTs extraction in our experiments based on environment domain corpus.
  • Keywords
    feature extraction; information filtering; natural language processing; statistical analysis; MWT; POS; arabic multiword terms; automatic extraction; linguistic filter; log likelihood ratio; multiword terms; part of speech; statistical filter; syntactic patterns; Barium; Computer science; Information technology; Iron; Syntactics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Information Technology (IMCSIT), Proceedings of the 2010 International Multiconference on
  • Conference_Location
    Wisla
  • ISSN
    2157-5525
  • Print_ISBN
    978-1-4244-6432-6
  • Type

    conf

  • DOI
    10.1109/IMCSIT.2010.5679929
  • Filename
    5679929