Detecting deception in reputation management
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
TRAVOS: Trust and Reputation in the Context of Inaccurate Information Sources
Autonomous Agents and Multi-Agent Systems
A context-aware approach for service selection using ontologies
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Ontology-Based Service Representation and Selection
IEEE Transactions on Knowledge and Data Engineering
Journal of Theoretical and Applied Electronic Commerce Research
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Experience-based service selection refers to selection of service providers using others' experiences . An agent can represent its experience (its demand and received service) rigorously using an ontology. When agents report their experiences truthfully, experience-based service selection outperforms classical rating-based service selection, in which agents only report ratings for service providers. However, in many setting agents may prefer to lie about their experiences. This paper tackles the problem of handling deceptive information in the context of experience-based service selection. We apply three current approaches for filtering unfair ratings to filtering deceptive experience. We analyze these approaches when multiagent systems have different types of liars and report their performance in filtering deceptive experiences.