• DocumentCode
    2418889
  • Title

    A Concept Similarity Based Text Classification Algorithm

  • Author

    Peng, Jing ; Yang, Dong-Qing ; Tang, Shi-Wei ; Gao, Jun ; Zhang, Peng-Yi ; Fu, Yan

  • Author_Institution
    Peking Univ., Beijing
  • Volume
    1
  • fYear
    2007
  • fDate
    24-27 Aug. 2007
  • Firstpage
    535
  • Lastpage
    539
  • Abstract
    Text classification is an important task of data mining. Existing algorithms, which based on vector space models, does not considered concept similarities among words, so the accuracy of traditional text classification cannot guarantee. To solve the problem, this paper proposes a new text classification algorithm in Chinese text processing based on concept similarity. The contributions of the paper include: (1) proposing a new similarity-computing model between words or sentences based on concept similarity; (2) applying the algorithm successfully in the text classification of WEB news; (3). analyzing the similarity computing formulas systematically in theory; (4).proving that the algorithm has much more accurate than traditional k-NN algorithm in text classification problems through extensive experiments.
  • Keywords
    data mining; natural language processing; text analysis; Chinese text processing; WEB news; concept similarity-based text classification algorithm; data mining; similarity computing; similarity-computing model; vector space models; Classification algorithms; Computer science; Data mining; Machine learning; Natural languages; Nearest neighbor searches; Statistical learning; Supervised learning; Text categorization; Text processing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems and Knowledge Discovery, 2007. FSKD 2007. Fourth International Conference on
  • Conference_Location
    Haikou
  • Print_ISBN
    978-0-7695-2874-8
  • Type

    conf

  • DOI
    10.1109/FSKD.2007.11
  • Filename
    4405982