• DocumentCode
    3418293
  • Title

    A graph-based web usage mining method considering client side data

  • Author

    Heydari, Mehdi ; Helal, Raed Ali ; Ghauth, Khairil Imran

  • Author_Institution
    Fac. of Inf. Technol., Multimedia Univ., Cyberjaya, Malaysia
  • Volume
    01
  • fYear
    2009
  • fDate
    5-7 Aug. 2009
  • Firstpage
    147
  • Lastpage
    153
  • Abstract
    To improve Web site, we need to evaluate current usage of it. Web usage mining and statistical analysis are two ways to evaluate usage of Web site. The combination of Web usage mining and statistical analysis gives more accurate information about Web usage. Through Web usage mining methods, graph mining covers complex Web browsing behaviors such as parallel browsing. Through statistical analysis methods, analyzing page browsing time gives valuable information about Web site and its users. This paper presents a Web usage mining method which combines Web usage mining and statistical analysis considering client side data. In other words, it combines graph based Web usage mining and browsing time analysis with taking client side data into account. It helps us to reconstruct user session exactly as it has been and based on these data, we find Web usage patterns with more accuracy.
  • Keywords
    Web sites; data mining; statistical analysis; Web browsing behaviors; Web site; client side data; graph-based Web usage mining method; parallel browsing; statistical analysis; Data mining; File servers; Informatics; Information analysis; Information technology; Navigation; Statistical analysis; Switches; Web page design; Web server; Client Side Web Usage Data; Graph Based Web Usage Mining; Page Browsing Time;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical Engineering and Informatics, 2009. ICEEI '09. International Conference on
  • Conference_Location
    Selangor
  • Print_ISBN
    978-1-4244-4913-2
  • Type

    conf

  • DOI
    10.1109/ICEEI.2009.5254802
  • Filename
    5254802