Summary
E-Commerce recommender systems provide customers with useful suggestions about available products. However, in presence of a high number of interactions between customers and Web sites, the generation of recommendations could become a heavy task. Moreover, customers often navigate on the Web using different devices whose different characteristics may influence customer’s preferences. In this paper we propose a new multi-agent system in which each device exploited by a customer is associated with a software agent which autonomously monitors the customer’s behaviour. The use of device agents leads to generate recommendations taking into account the exploited device, while the fully decentralized architecture introduces a strong reduction of the time costs.
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Rosaci, D., Sarné, G.M.L. (2008). A Multi-agent Recommender System for Supporting Device Adaptivity in E-Commerce. In: Badica, C., Mangioni, G., Carchiolo, V., Burdescu, D.D. (eds) Intelligent Distributed Computing, Systems and Applications. Studies in Computational Intelligence, vol 162. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85257-5_33
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DOI: https://doi.org/10.1007/978-3-540-85257-5_33
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-85256-8
Online ISBN: 978-3-540-85257-5
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