Trust Derivation and Transitivity in a Recommendation Trust Model

Recommendation-based trust models have emerged as an important risk management mechanism in E-commerce and online environments. This paper presents a trust model with trust derivation and transitivity based on subjective logic and the theory of collaborative filtering. For dealing with trust derivations, the theory of subjective logic is used to translate similarity taken from Collaborative Filtering(CF) into trust to form the potential trust between the correlated entities. In addition, we intend to describe a notation for specifying topologies of transitive trust, and to discuss ways to set up trust graph. The trust that the first entity should place on the distant one is derived through the trust graph. Finally, by transforming the value back into similarity measure terms, it could then be made appropriate for use in CF schemes. We present the test methods and their results to illustrate the accuracy and effectiveness of the approach.