GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
An algorithmic framework for performing collaborative filtering
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Communications of the ACM
Item-based collaborative filtering recommendation algorithms
Proceedings of the 10th international conference on World Wide Web
Privacy in browser-based attribute exchange
Proceedings of the 2002 ACM workshop on Privacy in the Electronic Society
An architecture for privacy-sensitive ubiquitous computing
Proceedings of the 2nd international conference on Mobile systems, applications, and services
SOUPS '05 Proceedings of the 2005 symposium on Usable privacy and security
Privacy and identity management for everyone
Proceedings of the 2005 workshop on Digital identity management
OpenID 2.0: a platform for user-centric identity management
Proceedings of the second ACM workshop on Digital identity management
A survey of trust and reputation systems for online service provision
Decision Support Systems
A Privacy Oriented Extension of Attribute Exchange in Shibboleth
SAINT-W '07 Proceedings of the 2007 International Symposium on Applications and the Internet Workshops
Privacy Oriented Attribute Exchange in Shibboleth Using Magic Protocols
SAINT '08 Proceedings of the 2008 International Symposium on Applications and the Internet
A Customer-Centric Privacy Protection Framework for Mobile Service-Oriented Architectures
SCC '08 Proceedings of the 2008 IEEE International Conference on Services Computing - Volume 2
Architecture and algorithms for a distributed reputation system
iTrust'03 Proceedings of the 1st international conference on Trust management
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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.