• DocumentCode
    1965904
  • Title

    Using semantic information for web usage mining based recommendation

  • Author

    Salin, Suleyman ; Senkul, Pinar

  • Author_Institution
    Comput. Eng. Dept., Middle East Tech. Univ., Ankara, Turkey
  • fYear
    2009
  • fDate
    14-16 Sept. 2009
  • Firstpage
    236
  • Lastpage
    241
  • Abstract
    Web usage mining has become popular in various business areas related with Web site development. In Web usage mining, commonly visited navigational paths are extracted in terms of Web page addresses from the Web server visit logs, and the patterns are used in various applications including recommendation. The semantic information of the Web page contents is generally not included in Web usage mining. In this work, a framework for integrating semantic information with Web usage mining is presented. The frequent navigational patterns are extracted in the form of ontology instances instead of Web page addresses and the result is used for generating Web page recommendations to the visitor. In addition, an evaluation mechanism is implemented in order to test the success of the recommendation. Test results show that more accurate recommendations can be obtained by including semantic information in the Web usage mining.
  • Keywords
    Web sites; data mining; information filters; semantic Web; Web page addresses; Web server; Web site development; Web usage mining based recommendation; frequent navigational patterns; ontology; semantic information; Classification algorithms; Frequency; Graphical models; Induction generators; Linear discriminant analysis; Performance gain; Statistics; Support vector machine classification; Support vector machines; Text categorization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer and Information Sciences, 2009. ISCIS 2009. 24th International Symposium on
  • Conference_Location
    Guzelyurt
  • Print_ISBN
    978-1-4244-5021-3
  • Electronic_ISBN
    978-1-4244-5023-7
  • Type

    conf

  • DOI
    10.1109/ISCIS.2009.5291819
  • Filename
    5291819