• DocumentCode
    2119650
  • Title

    The Method of Text Categorization on Imbalanced Datasets

  • Author

    Xin-fu, Li ; Yan, Yu ; Peng, Yin

  • Author_Institution
    Coll. of Math. & Comput. Sci., Hebei Univ., Baoding
  • fYear
    2009
  • fDate
    27-28 Feb. 2009
  • Firstpage
    650
  • Lastpage
    653
  • Abstract
    In practical applications, datasets are usually imbalanced, but traditional approaches usually lead a low recognition rate. To address this problem, in this paper, over-sampling of the minority class has been proposed to increase the number of minority class, so as to achieve balance, thereby enhancing recognition rate of minority class. The experiments show that this approach achieved satisfactory results.
  • Keywords
    classification; text analysis; imbalanced dataset; minority class recognition; text categorization; Application software; Artificial intelligence; Computer science; Educational institutions; Information retrieval; Machine learning; Mathematics; Seminars; Text categorization; Text recognition; SVM; TF-IDF; imbalanced dataset; text categorization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communication Software and Networks, 2009. ICCSN '09. International Conference on
  • Conference_Location
    Macau
  • Print_ISBN
    978-0-7695-3522-7
  • Type

    conf

  • DOI
    10.1109/ICCSN.2009.70
  • Filename
    5076934