A Game Theory-Based Approach to Service Rating

Most recommender systems proposed for service computing do not address the attacks on service rating systems. This paper proposed a service rating system that is capable of countering malicious manipulations. The system predicts how customers rate services based on the ratings given by the similar users of the customers and the trustworthy experienced users. The proposed scheme uses the collaborative filtering technique and a game theory-based approach in choosing users for rating prediction. Compared with existing schemes, the proposed scheme is more effective in countering malicious manipulations.