Fine-Grained Recommendation Systems for Service Attribute Exchange

The effectiveness of service oriented computing relies on the trustworthiness of sharing of data between services. We advocate a semi-automated approach for information distribution and sharing, assisted by a reputation system. Unlike current recommendation systems which provide a user with a general trust value for a service, we propose a reputation model which calculates trust neighbourhoods through fine-grained multi-attribute analysis. Such a model allows a recommendation relevance to improve whilst maintaining a large user group, propagating and evolving trust perceptions between users. The approach is demonstrated on a small example.