E-commerce Reputation Modeling Based on Fuzzy Relation

For the vague nature of trust and reputation, the traditional reputation modelings used the classic probability or fuzzy sets to describe and measure the degree of trust. The theoretic foundation of these models is subject logic or fuzzy logic. But in some practical applications, the usage of simple probability model led trust´s subjectivity and uncertainty to randomness. For the fuzzy logic, the determination of membership functions associated with vague concepts is difficult or impossible. In this paper, we present a new reputation modeling based on the fuzzy relation (called RMBFR) which is utilized to represent the semantic relation among linguistic words. We define reputation degree computing in this paper according trust passing and trust combination; we show that the RMBFR satisfies some perfect properties, e.g. the excluded middle law, law of non-contradiction. Finally, an e-commerce behavioral decision example is described to show RMBFR´s practical application.