• DocumentCode
    2752677
  • Title

    Research on Text-Reducing Method Based on the Improved KNN Algorithm

  • Author

    Liu, Peiyu ; Qiu, Ye ; Zhao, Lina

  • Author_Institution
    Sch. of Inf. Sci. & Eng., Shandong Normal Univ., Jinan, China
  • Volume
    4
  • fYear
    2009
  • fDate
    14-16 Aug. 2009
  • Firstpage
    581
  • Lastpage
    585
  • Abstract
    There are relevance and redundancy of the feature words in the text vector space, so we proposed a text-reducing method based on the improved KNN algorithm in this paper. Vector polymer theory and feature selection methods were used to reducing the dimension of vector space. Feature words would have more ability to represent categories after feature selection. Experiments proved, the improved KNN algorithm were used in text-reducing not only can reducing the dimension of vector space more effectively, but also can improving the speed and accuracy of the text classify.
  • Keywords
    feature extraction; pattern classification; text analysis; feature selection methods; feature words; improved KNN algorithm; text classify; text vector space; text-reducing method; vector polymer theory; Fuzzy systems; Independent component analysis; Information science; Internet; Knowledge engineering; Polymers; Principal component analysis; Space technology; Sparse matrices; Statistical analysis; feature selection; similarity degree; text-reducing; vector polymerization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09. Sixth International Conference on
  • Conference_Location
    Tianjin
  • Print_ISBN
    978-0-7695-3735-1
  • Type

    conf

  • DOI
    10.1109/FSKD.2009.616
  • Filename
    5359247