Abstract
Most of recommendation systems work with traditional recommender algorithms such as collaborative filtering. Recently context has been incorporated in these algorithms as a fundamental factor to improve the quality of recommendations provided in the context of the user. Context is used as a filter for selecting items suitable for the current situation of the user. This work contributes to the improvement of contextual recommendations through the proposed method that uses a pre-filtering approach, traditional collaborative filtering and fuzzy rules. The Movie lens dataset was used for testing the method and the experiments conducted show promising results.
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Ramirez-Garcia, X., Garcia-Valdez, M. (2015). A Pre-filtering Based Context-Aware Recommender System using Fuzzy Rules. In: Melin, P., Castillo, O., Kacprzyk, J. (eds) Design of Intelligent Systems Based on Fuzzy Logic, Neural Networks and Nature-Inspired Optimization. Studies in Computational Intelligence, vol 601. Springer, Cham. https://doi.org/10.1007/978-3-319-17747-2_38
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DOI: https://doi.org/10.1007/978-3-319-17747-2_38
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