• DocumentCode
    1670947
  • Title

    User interest discovery based on Web Usage Mining

  • Author

    Bin, Jia ; Jian-guo, Xu ; Xu, Chang

  • Author_Institution
    College of Information and Engineering, Shan Dong University of Science and Technology, Qingdao. China
  • fYear
    2011
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    According to the user´s access sequence, whether clustering can extracte the effectively user´s interest model is closely related to the algorithm of identifying user´s access affairs and clustering. This paper fully consider the impact on user interest mining of the topology and order of web papers. So, this paper advanced AER algorithm, new similarity formula and FCR algorithm. Finally, this paper tested and verified the AER algorithm and FCR algorithm.
  • Keywords
    Clustering algorithms; Computational modeling; Computer integrated manufacturing; Computers; Data mining; Data models; Educational institutions; clustering; similarity; user interest discovery; web usage mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    E -Business and E -Government (ICEE), 2011 International Conference on
  • Conference_Location
    Shanghai, China
  • Print_ISBN
    978-1-4244-8691-5
  • Type

    conf

  • DOI
    10.1109/ICEBEG.2011.5886765
  • Filename
    5886765
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1670947