MASHA: A multi-agent system handling user and device adaptivity of Web sites
User Modeling and User-Adapted Interaction
Web site personalization based on link analysis and navigational patterns
ACM Transactions on Internet Technology (TOIT)
Usage-based web recommendations: a reinforcement learning approach
Proceedings of the 2007 ACM conference on Recommender systems
EC-XAMAS: SUPPORTING E-COMMERCE ACTIVITIES BY AN XML-BASED ADAPTIVE MULTI-AGENT SYSTEM
Applied Artificial Intelligence
Trust management tools for internet applications
iTrust'03 Proceedings of the 1st international conference on Trust management
Recommendation of similar users, resources and social networks in a Social Internetworking Scenario
Information Sciences: an International Journal
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This paper proposes DESIRE, a multi-agent system that exploits dependability to provide users, operating in a social internetworking scenario, with high-quality recommendations. DESIRE is based on an innovative social internetworking model that handles both dependability and reputation of its users, as well as their opinions about available resources.