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
Link To Document