• DocumentCode
    3230545
  • Title

    A PSO-Based Web Document Classification Algorithm

  • Author

    Wang, Ziqiang ; Zhang, Qingzhou ; Zhang, Dexian

  • Author_Institution
    Henan Univ. of Technol., Zhengzhou
  • Volume
    3
  • fYear
    2007
  • fDate
    July 30 2007-Aug. 1 2007
  • Firstpage
    659
  • Lastpage
    664
  • Abstract
    Due to the exponential growth of documents in the Internet and the emergent need to organize them, the automatic document classification has received an ever-increased attention in the recent years. The particle swarm optimization (PSO) algorithm, new to the document classification community, is a robust stochastic evolutionary algorithm based on the movement and intelligence of swarms. In this paper, a PSO-based algorithm for document classification is presented. Comparison between our method and other conventional document classification algorithms is conducted on Reuter and TREC corpora. The experimental results indicate that our proposed algorithm yields much better performance than other conventional algorithms.
  • Keywords
    Internet; classification; document handling; evolutionary computation; particle swarm optimisation; Internet; PSO-based Web document classification algorithm; automatic document classification; particle swarm optimization; robust stochastic evolutionary algorithm; Artificial intelligence; Classification algorithms; Classification tree analysis; Databases; Evolutionary computation; Genetic algorithms; Internet; Neural networks; Particle swarm optimization; Software engineering;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, 2007. SNPD 2007. Eighth ACIS International Conference on
  • Conference_Location
    Qingdao
  • Print_ISBN
    978-0-7695-2909-7
  • Type

    conf

  • DOI
    10.1109/SNPD.2007.72
  • Filename
    4287933