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.

Rosaci, D., Sarne', G. (2014). REBECCA: A Trust-Based Filtering to Improve Recommendations for B2C e-Commerce. In Intelligent Distributed Computing VII (pp.31-36). Berlin : Springer [10.1007/978-3-319-01571-2_5].

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

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.
paper
Multi-agent system; Trust system; e.Commerce;
English
7th International Symposium on Intelligent Distributed Computing - IDC 2013
04-06/09/2013
Zavoral F Jung J Badica C
Intelligent Distributed Computing VII
978-3-319-01570-5
2014
511
31
36
http://link.springer.com/chapter/10.1007/978-3-319-01571-2_5#
open
Rosaci, D., Sarne', G. (2014). REBECCA: A Trust-Based Filtering to Improve Recommendations for B2C e-Commerce. In Intelligent Distributed Computing VII (pp.31-36). Berlin : Springer [10.1007/978-3-319-01571-2_5].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/299404
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