• DocumentCode
    1672037
  • Title

    Personalized Recommendation Algorithm based on SVM

  • Author

    Wu, Bing ; Qi, Luo ; Feng, Xiong

  • Author_Institution
    Wuhan Univ. of Technol., Wuhan
  • fYear
    2007
  • Firstpage
    951
  • Lastpage
    953
  • Abstract
    With the development of the E-commerce, personalized product and service have become a developing trend gradually .To meet the personalized needs of customers in E-commerce, a new personalized 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 was adopted for collaborative recommendation in classification mode, and then Vector Space Model 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. The algorithm could also used in personalized recommendation service system based on E-commerce.
  • Keywords
    electronic commerce; support vector machines; E-commerce; SVM; atomic information; collaborative recommendation; content-based recommendation; personalized recommendation algorithm; support vector machine; vector space model; Algorithm design and analysis; Collaboration; Engineering management; Feedback; Geographic Information Systems; Large-scale systems; Paper technology; Support vector machine classification; Support vector machines; Technology management;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications, Circuits and Systems, 2007. ICCCAS 2007. International Conference on
  • Conference_Location
    Kokura
  • Print_ISBN
    978-1-4244-1473-4
  • Type

    conf

  • DOI
    10.1109/ICCCAS.2007.4348205
  • Filename
    4348205