TRES: A Decentralized Agent-Based Recommender System to Support B2C Activities

  • Domenico Rosaci
  • Giuseppe M. L. Sarné
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5559)


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.


Interest Rate Recommender System Product Category Recommendation Algorithm Product Instance 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Domenico Rosaci
    • 1
  • Giuseppe M. L. Sarné
    • 1
  1. 1.DIMETUniversità Mediterranea di Reggio CalabriaReggio CalabriaItaly

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