• DocumentCode
    2238049
  • Title

    Personalized Recommendation Algorithm Research Based on Multi-agent

  • Author

    Zhu, Hai ; Song, Xiaoli ; Zhang, Shiju ; Gao, Yan ; Zhang, Panke

  • Author_Institution
    Econ. & Adm. Coll., Henan Univ. of Sci. & Technol., Luoyang
  • Volume
    2
  • fYear
    2008
  • fDate
    19-19 Dec. 2008
  • Firstpage
    177
  • Lastpage
    180
  • Abstract
    In order to meet the accuracy need of network users on information service, this paper introduces multi- agent feedback learning mechanism based on traditional collaborative filtering algorithms and proposes recommendation algorithm based on multi-agent. During the recommendation process, the algorithm, considering the recommended project as a recommended subject, infers autonomously whether the recommended project fits the target users. Meanwhile, the recommended subject can also improve recommendation precision by active learning based on userpsilas feedback. The recommendation algorithm can be finely applied to library recommender system and partial E-commerce recommender system.
  • Keywords
    information filtering; multi-agent systems; user interfaces; active learning; collaborative filtering algorithms; e-commerce recommender system; information service; library recommender system; multiagent feedback learning mechanism; network users; personalized recommendation algorithm; recommendation process; user feedback; Collaboration; Databases; Educational institutions; Feedback; Filtering algorithms; History; Internet; Recommender systems; Search engines; Seminars; Multi-agent; Recommendation Engine; User Interest;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Business and Information Management, 2008. ISBIM '08. International Seminar on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-0-7695-3560-9
  • Type

    conf

  • DOI
    10.1109/ISBIM.2008.69
  • Filename
    5116450