TRUST MODEL FOR HIGH QUALITY RECOMMENDATION

摘要

In this paper, we propose a trust management model for decentralised systems that improves the quality of recommendations that members of a virtual community get about the trustworthiness of objects. In our system, as in well-known solutions, members of the community evaluate (i) the functional trust in an item by the analysis of the object's qualities, past experience, and recommendations and (ii) the referral trust in a recommender by the analysis of the recommender's qualities and reputation based on personal experience. Moreover, in our trust model, each principal debates with its recommenders about the justifications given to support a recommendation. Thus, the usefulness and the reliability of a recommendation depend also on the strength of the arguments supporting the recommendation. A measure of this strength results after the member has played an argumentation game with the recommender. Therefore, the recommendations that are taken into account are those which better match the member's profile and way of reasoning. Our trustworthiness evaluation algorithm is context dependent and able to collect both direct and indirect information about trustees. Our trust model is part of an agent-based architecture we propose for decentralised virtual communities. This architecture provides our system with autonomy, unobtrusiveness, user mobility, and context-awareness.