• DocumentCode
    3306437
  • Title

    A Recommendation Trust Model Based on E-commerce Transactions Content-Similarity

  • Author

    Wang, Gang ; Gui, XiaoLin ; Wei, GuangFu

  • Author_Institution
    Sch. of Electron. & Inf. Eng., Xi´´an JiaoTong Univ., Xi´´an, China
  • fYear
    2010
  • fDate
    24-25 April 2010
  • Firstpage
    105
  • Lastpage
    108
  • Abstract
    This paper proposes a new recommendation trust model, which is based on E-Commerce transaction content similarity and differentiates the trust degree of acquaintance node recommendation from stranger node recommendation (hereinafter referred to as TCSRTrust). The TCSRTrust model eliminates a subjective hypothesis that recommendation of a trustworthy node is the more trustworthy in previous global trust models, as the subjective hypothesis is not to conform to actualities in the current large-scale distributed network environment, and objectivity and reliability can not be guaranteed as a result. In contrast, simulation experiments prove that the TCSRTrust Model conforms better to the current new network application environment, and that the TCSRTrust Model brings greater improvement and enhancement in such broader security issues as fending off malicious node slanders and containing collaborative cheating.
  • Keywords
    Collaboration; Counting circuits; Electronic commerce; Large-scale systems; Machine vision; Man machine systems; Ontologies; Solid modeling; Ubiquitous computing; Virtual environment; Domain Ontology; E-Commerc; Reputation Recommendation; Similarity Degree; Trust;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Vision and Human-Machine Interface (MVHI), 2010 International Conference on
  • Conference_Location
    Kaifeng, China
  • Print_ISBN
    978-1-4244-6595-8
  • Electronic_ISBN
    978-1-4244-6596-5
  • Type

    conf

  • DOI
    10.1109/MVHI.2010.101
  • Filename
    5532659