Implicit user credibility extraction for reputation rating mechanism in B2C e-commerce

Reputation systems are emerging as one of the promising solutions for building trust among market participants in e-commerce. Finding ways to avoid or reduce the influence of unfair ratings is a fundamental problem in reputation systems. We propose an implicit reputation rating mechanism suitable for B2C e-commerce. The conceptual framework of the mechanism is based on the source credibility model in consumer psychology. We have experimentally evaluated the performance of the mechanism by comparing with the other benchmark rating mechanisms. The experimental results provide evidence that the general users' opinions can be predicted more effectively by only a small number of users selected by our proposed mechanism.

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