PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Perseus - A Personalized Reputation System
Petteri Nurmi
In: The 2007 IEEE/WIC/ACM International Conference on Web Intelligence, 2-5 Nov 2007, Fremont, California.

Abstract

We propose Perseus, a personalized reputation system. In Perseus, reputations comprise of three aspects: how much I personally trust another individual, how trustworthy others think the individual is, and how much I trust the opinions of others. Perseus is adaptive in the sense that user feedback is used to modify the way the different aspects are considered. We also present simulation experiments, which indicate that Perseus is robust and able to survive under extreme conditions of misbehavior. In addition, Perseus encourages individuals to rate the other party and give fair ratings. We also compare Perseus against other well-known reputation systems.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:User Modelling for Computer Human Interaction
Learning/Statistics & Optimisation
ID Code:3565
Deposited By:Petteri Nurmi
Deposited On:12 February 2008