Recommender systems usually support B2C e-Commerce activities without to provide e-buyers with information about the reputation of both products and interlocutors. To provide B2C traders with suggestions taking into account gossips, in this paper we present REBECCA, a fully decentralized trust-based B2C recommender system that also guarantees scalability and privacy. Some experiments show the advantages introduced by REBECCA in generating more effective suggestions.

REBECCA: A Trust-Based Filtering to Improve Recommendations for B2C e-Commerce

ROSACI D;SARNE' G
2014

Abstract

Recommender systems usually support B2C e-Commerce activities without to provide e-buyers with information about the reputation of both products and interlocutors. To provide B2C traders with suggestions taking into account gossips, in this paper we present REBECCA, a fully decentralized trust-based B2C recommender system that also guarantees scalability and privacy. Some experiments show the advantages introduced by REBECCA in generating more effective suggestions.
978-3-319-01570-5
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.12318/17982
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