• DocumentCode
    2728938
  • Title

    Recognising Professional-Activity Groups and Web Usage Mining for Web Browsing Personalisation

  • Author

    Mrabet, Yassine ; Khelif, Khaled ; Dieng-Kuntz, Rose

  • Author_Institution
    INRIA Sophia Antipolis, Nice
  • fYear
    2007
  • fDate
    2-5 Nov. 2007
  • Firstpage
    719
  • Lastpage
    722
  • Abstract
    Web usage mining can play an important role in supporting the navigation on the future Web. In fact detection of common or professional profiles allows browsers and web sites to personalise the user session and to recommend specific resources to the interested people. Semantic web approach seems interesting for this task. We propose in this paper a generic approach for profile detection relying on semantic web technologies. It takes advantages from ontologies, semantic annotations on web resources and inference engines.
  • Keywords
    data mining; online front-ends; search engines; semantic Web; Web browsing personalisation; Web resources; Web sites; Web usage mining; inference engines; ontologies; professional-activity groups; profile detection; semantic Web; semantic annotations; Buildings; Electronic equipment testing; Engines; Intelligent networks; Kernel; Keyword search; Navigation; Ontologies; Semantic Web; Software libraries; annotations; ontologies; profile learning; semantic web browsing.;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Web Intelligence, IEEE/WIC/ACM International Conference on
  • Conference_Location
    Fremont, CA
  • Print_ISBN
    978-0-7695-3026-0
  • Type

    conf

  • DOI
    10.1109/WI.2007.46
  • Filename
    4427179