• DocumentCode
    2095035
  • Title

    Website Structure Optimization Technology Based on Customer Interest Clustering Algorithm

  • Author

    Cheng, Shutong ; Xu, Congfu ; Dan, Hongwei

  • Author_Institution
    Coll. of Comput. Sci., Zhejiang Univ., Hangzhou, China
  • Volume
    1
  • fYear
    2008
  • fDate
    20-22 Dec. 2008
  • Firstpage
    802
  • Lastpage
    804
  • Abstract
    Based on an analysis on the Web log mining algorithm of predecessors, this paper presents the Web site structure optimization technology to improve customer interest. The technology proposes similar customer groups and clustering algorithms of relevant Web pages based on interest matrix of customers accessing a Web site to discover the hidden customer access patterns. Experiment results demonstrate the effectiveness of our algorithms.
  • Keywords
    Web sites; customer satisfaction; data mining; matrix algebra; optimisation; Web log mining algorithm; Web site structure optimization; customer access pattern; customer interest clustering algorithm; customer interest matrix; Algorithm design and analysis; Association rules; Attenuation; Clustering algorithms; Computer science; Data mining; Educational institutions; Partitioning algorithms; Uniform resource locators; Web pages; Clustering; Interest Matrix; Website Structure Optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Computational Technology, 2008. ISCSCT '08. International Symposium on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-3746-7
  • Type

    conf

  • DOI
    10.1109/ISCSCT.2008.124
  • Filename
    4731545