• DocumentCode
    602543
  • Title

    Neural networks for the automation of Arabic text categorization

  • Author

    Alsaleem, S.M.

  • Author_Institution
    King Saud Univ., Riyadh, Saudi Arabia
  • fYear
    2013
  • fDate
    20-22 Jan. 2013
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    In this paper, we compare and investigate Naive Bayesian Method (NB), K-Nearest Neighbor along with Neural Network method on different Arabic data sets. The bases of our comparison are the most popular text evaluation measures. The Experimental results against different Arabic text categorization data sets reveal that NB categorizer outperformed both k-NN and NN algorithms with regard to Fl. Recall and Precision measures.
  • Keywords
    belief networks; neural nets; text analysis; K-nearest neighbor algorithm; Naïve Bayesian method; arabic text categorization automation; data set; k-NN algorithm; neural network; text evaluation measures; Accuracy; Artificial neural networks; Classification algorithms; Information retrieval; Niobium; Text categorization; Information Retrieval; K-Nearest Neighbor; Machine Learning; Naive Bayesian; Neural Network; Text Categorization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Applications Technology (ICCAT), 2013 International Conference on
  • Conference_Location
    Sousse
  • Print_ISBN
    978-1-4673-5284-0
  • Type

    conf

  • DOI
    10.1109/ICCAT.2013.6522022
  • Filename
    6522022
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=602543