• DocumentCode
    253486
  • Title

    System for fuzzy document clustering and fast fuzzy classification

  • Author

    Rojcek, Michal

  • Author_Institution
    Dept. of Inf., Catholic Univ. in Ruzomberok, Ružomberok, Slovakia
  • fYear
    2014
  • fDate
    19-21 Nov. 2014
  • Firstpage
    39
  • Lastpage
    42
  • Abstract
    The paper introduces uncontrolled fuzzy document clustering and fast fuzzy classification. This system is based on KMART neural network that realizes clustering, and original Fuzzy classification algorithm on the base of Fuzzy ART network that realizes classification. Both algorithms share their weights. Uncontrolled system has two separate flows: by first one we influence structure of categories (plasticity) and second one classifies without possibility to influence defined structure (stability). The paper shows legitimacy of such an approach with regard on quality and speed of classification.
  • Keywords
    ART neural nets; document handling; fuzzy set theory; pattern classification; pattern clustering; KMART neural network; classification quality; classification speed; fast fuzzy classification; fuzzy ART network; fuzzy classification algorithm; uncontrolled fuzzy document clustering; uncontrolled system; Adaptive systems; Classification algorithms; Clustering algorithms; Neural networks; Subspace constraints; Testing; Training;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Informatics (CINTI), 2014 IEEE 15th International Symposium on
  • Conference_Location
    Budapest
  • Type

    conf

  • DOI
    10.1109/CINTI.2014.7028711
  • Filename
    7028711