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Gradual trust and distrust in recommender systems. Fuzzy Sets and Systems

By Patricia Victor, Chris Cornelis, Martine De Cock and Paulo Pinheiro Da Silva B

Abstract

Trust networks among users of a recommender system (RS) prove beneficial to the quality and amount of the recommendations. Since trust is often a gradual phenomenon, fuzzy relations are the pre-eminent tools for modeling such networks. However, as current trust-enhanced RSs do not work with the notion of distrust, they cannot differentiate unknown users from malicious users, nor represent inconsistency. These are serious drawbacks in large networks where many users are unknown to each other and might provide contradictory information. In this paper, we advocate the use of a trust model in which trust scores are (trust,distrust)-couples, drawn from a bilattice that preserves valuable trust provenance information including gradual trust, distrust, ignorance, and inconsistency. We pay particular attention to deriving trust information through a trusted third party, which becomes especially challenging when also distrust is involved

Topics: addresses
Year: 2009
OAI identifier: oai:CiteSeerX.psu:10.1.1.183.1880
Provided by: CiteSeerX
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