Abstract
Nowadays, many e-Commerce tools support customers with automatic recommendations. Many of them are centralized and lack in efficiency and scalability, while other ones are distributed and require a computational overhead excessive for many devices. Moreover, all the past proposals are not “open” and do not allow new personalized terms to be introduced into the domain ontology. In this paper, we present a distributed recommender, based on a multi-tiered agent system, trying to face the issues outlined above. The proposed system is able to generate very effective suggestions without a too onerous computational task. We show that our system introduces significant advantages in terms of openess, privacy and security.
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Palopoli, L., Rosaci, D., Sarné, G.M.L. (2013). A Multi-tiered Recommender System Architecture for Supporting E-Commerce. In: Fortino, G., Badica, C., Malgeri, M., Unland, R. (eds) Intelligent Distributed Computing VI. Studies in Computational Intelligence, vol 446. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32524-3_10
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DOI: https://doi.org/10.1007/978-3-642-32524-3_10
Publisher Name: Springer, Berlin, Heidelberg
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