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A RBN-based recommender system architecture

Abstract : With the widespread use of Internet, recommender systems are becoming increasingly adapted to resolve the problem of information overload and to deal with large amount of on line information. Several approaches and techniques have been proposed to implement recommender systems. Most of them rely on flat data representation while most real world data are stored in relational databases. This paper proposes a new recommendation approach that explores the relational nature of the data in hand using relational Bayesian networks (RBNs).
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https://hal.archives-ouvertes.fr/hal-00812168
Contributor : Philippe Leray Connect in order to contact the contributor
Submitted on : Friday, April 17, 2020 - 3:32:05 PM
Last modification on : Wednesday, April 27, 2022 - 4:37:56 AM

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Mouna Ben Ishak, Nahla Ben Amor, Philippe Leray. A RBN-based recommender system architecture. International Conference on Modeling, Simulation and Applied Optimization (ICMSAO 2013), 2013, Hammamet, Tunisia. pp.1-6, ⟨10.1109/ICMSAO.2013.6552609⟩. ⟨hal-00812168⟩

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