Abstract
This paper presents and describes the construction of a recommender system model that classifies input information to yield product recommendations. This model was applied within the contents industry [1] by using artificial neural networks (particularly adaptive resonance theory) as an intelligent agent. The Netflix Prize data base was used and the model’s validation and simulation was written using Matlab®.
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Bermudez, G.M.T., Espada, J.P., Nuñez-Valdez, E.R. (2014). An Application for Recommender Systems in the Contents Industry. In: Uden, L., Wang, L., Corchado Rodríguez, J., Yang, HC., Ting, IH. (eds) The 8th International Conference on Knowledge Management in Organizations. Springer Proceedings in Complexity. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-7287-8_26
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DOI: https://doi.org/10.1007/978-94-007-7287-8_26
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