• DocumentCode
    461697
  • Title

    Research on Adaptive Recommendation Algorithm in Personalized E-Supermarket Service System

  • Author

    Chen, Jingjing ; Luo, Qi

  • Author_Institution
    Dept. of Inf. Technol., Central China Normal Univ., Wuhan
  • Volume
    3
  • fYear
    2006
  • fDate
    16-20 2006
  • Abstract
    To meet the personalized needs of customers in E-supermarket, a new adaptive recommendation algorithm based on support vector machine was proposed in the paper. First, user profile was organized hierarchically into field information and atomic information needs, considering similar information needs in the group users. Support vector machine (SVM) was adopted for collaborative recommendation in classification mode, and then vector space model (VSM) was used for content-based recommendation according to atomic information needs. The algorithm had overcome the demerit of using collaborative or content-based recommendation solely, which improved the precision and recall in a large degree. It also fits for large scale group recommendation
  • Keywords
    groupware; retail data processing; support vector machines; SVM; adaptive recommendation algorithm; collaborative recommendation; content-based recommendation; customers; personalized E-supermarket service system; support vector machine; vector space model; Collaboration; Feedback; Information technology; Kernel; Large-scale systems; Marketing and sales; Support vector machine classification; Support vector machines; Web page design;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing, 2006 8th International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    0-7803-9736-3
  • Electronic_ISBN
    0-7803-9736-3
  • Type

    conf

  • DOI
    10.1109/ICOSP.2006.345769
  • Filename
    4129235