Novel and Classic Metaheuristics for Tunning a Recommender System for Predicting Student Performance in Online Campus

Juan Antonio Gómez Pulido, Enrique Cortés-Toro, Arturo Durán-Domínguez, Broderick Crawford, Ricardo Soto. Novel and Classic Metaheuristics for Tunning a Recommender System for Predicting Student Performance in Online Campus. In Hujun Yin, David Camacho, Paulo Novais, Antonio J. Tallón-Ballesteros, editors, Intelligent Data Engineering and Automated Learning - IDEAL 2018 - 19th International Conference, Madrid, Spain, November 21-23, 2018, Proceedings, Part I. Volume 11314 of Lecture Notes in Computer Science, pages 125-133, Springer, 2018. [doi]

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