Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
Communications of the ACM
Proceedings of the 11th international conference on World Wide Web
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 2
Reputation systems: an axiomatic approach
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Link analysis ranking: algorithms, theory, and experiments
ACM Transactions on Internet Technology (TOIT)
Ranking systems: the PageRank axioms
Proceedings of the 6th ACM conference on Electronic commerce
A trust-enhanced recommender system application: Moleskiing
Proceedings of the 2005 ACM symposium on Applied computing
Sybilproof reputation mechanisms
Proceedings of the 2005 ACM SIGCOMM workshop on Economics of peer-to-peer systems
Incentive compatible ranking systems
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Trust-based recommendation systems: an axiomatic approach
Proceedings of the 17th international conference on World Wide Web
Quantifying incentive compatibility of ranking systems
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Controversial users demand local trust metrics: an experimental study on Epinions.com community
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
An axiomatic approach to personalized ranking systems
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
On the axiomatic foundations of ranking systems
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
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The goal of a trust-based recommendation system is to generate personalized recommendations from known opinions and trust relationships. Prior work introduced the axiomatic approach to trust-based recommendation systems, but has been extremely limited by considering binary systems, while allowing these systems to be inconsistent. In this work we introduce an axiomatic approach to deal with consistent continuous trust-based recommendation systems. We introduce the model, discuss some basic axioms, and provide a characterization of a class of systems satisfying a set of basic axioms. In addition, as it turns out, relaxing some of the axioms leads to additional interesting systems, which we examine.