Agents that reduce work and information overload
Communications of the ACM
Information Retrieval
A Taxonomy of Recommender Agents on theInternet
Artificial Intelligence Review
Agents' roles in B2C e-commerce
AI Communications
Economics and Electronic Commerce: Survey and Directions for Research
International Journal of Electronic Commerce
Electronic Commerce and Organizational Innovation: Aspects and Opportunities
International Journal of Electronic Commerce
EC-XAMAS: SUPPORTING E-COMMERCE ACTIVITIES BY AN XML-BASED ADAPTIVE MULTI-AGENT SYSTEM
Applied Artificial Intelligence
Recommending multimedia web services in a multi-device environment
Information Systems
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The increasing relevance assumed by the E-Commerce in the Web community is attested by the great number of powerful and sophisticated tools developed in the last years to support traders in their commercial activities. In this scenario, recommender systems appear doubtless as a promising solution for supporting both customers' and merchants' activities. In this paper, we propose an agent-based recommender system, called TRES, able to help traders in Business-to-Consumer activities with useful and personalized suggestions based on interests and preferences stored in customers' profiles, adopting a fully decentralized architecture that suitably introduces in the system both scalability and privacy protection.