• DocumentCode
    169551
  • Title

    Building a syntactic rules-based stemmer to improve search effectiveness for arabic language

  • Author

    Cherif, Walid ; Madani, Abdellah ; Kissi, Mohamed

  • Author_Institution
    Dept. of Comput., Chouaib Doukkali Univ., El-Jadida, Morocco
  • fYear
    2014
  • fDate
    7-8 May 2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Nowadays, The world is experiencing a huge growth in the volume of exchanged texts, which makes some of it untapped. Text Mining is the set of techniques that analyze these large masses of information, extract relations that can be unknown beforehand and provide solutions that help decision making. In this sense, stemming is a common requirement of these techniques. It includes reducing different grammatical forms of a word and bringing them to a common base form. In what follows, we will discuss these treatment methods for arabic text, show their limits and provide new algorithm to improve them.
  • Keywords
    data mining; decision making; information retrieval; natural language processing; text analysis; Arabic language; Arabic text; decision making; different grammatical form reduction; information analysis; relation extraction; search effectiveness improvement; syntactic rules-based stemmer; text mining; Dictionaries; Text mining; arabic language; automatic language processing; light-stemming; stemming; text mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Systems: Theories and Applications (SITA-14), 2014 9th International Conference on
  • Conference_Location
    Rabat
  • Print_ISBN
    978-1-4799-3566-6
  • Type

    conf

  • DOI
    10.1109/SITA.2014.6847295
  • Filename
    6847295