• DocumentCode
    2406546
  • Title

    Web Page Classification Using Distributed Learning Automata and Partitioning Graph Algorithm

  • Author

    Bazarganigilani, Mahdi ; Syed, Ali

  • Author_Institution
    Fac. of Bus., Charles Sturt Univ., Melbourne, VIC, Australia
  • fYear
    2010
  • fDate
    Aug. 30 2010-Sept. 3 2010
  • Firstpage
    302
  • Lastpage
    304
  • Abstract
    The characteristic of dynamic websites is that they include hidden contents, and this huge repository is only accessible via the website interfaces. This is a vital capability of all search engines, thus providing the users with links that are more relevant and ranked according to their needs. The drawback of most search engine algorithms is that they rank pages based on hyperlinked relative importance to other pages, rather than user intent and interest. This paper proposes a method based on Learning Automata for the classification of the webpage searches.
  • Keywords
    Internet; graph theory; learning automata; pattern classification; search engines; user interfaces; Web page classification; Website interfaces; distributed learning automata; dynamic Websites characteristic; hidden contents; partitioning graph algorithm; rank pages; search engines; Classification algorithms; Clustering algorithms; Heuristic algorithms; Learning automata; Partitioning algorithms; Software algorithms; Web pages; Distributed Learning Automata; Graph Partitioning Algorithm; Web classification; component; web page ranking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Database and Expert Systems Applications (DEXA), 2010 Workshop on
  • Conference_Location
    Bilbao
  • ISSN
    1529-4188
  • Print_ISBN
    978-1-4244-8049-4
  • Type

    conf

  • DOI
    10.1109/DEXA.2010.66
  • Filename
    5591189