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An efficient recommender system method based on the numerical relevances and the non-numerical structures of the ratings
ArticleAbstract: In this paper, we propose a collaborative filtering method designed to improve the current memory-baPalabras claves:COLLABORATIVE FILTERING, model-based methods, pbkp_rediction time, performance, recommender systems, Similarity MeasuresAutores:Bobadilla J., Ortega F., Remigio Hurtado Ortiz, Zhu B.Fuentes:googlescopusArtificial Intelligence Scientific Documentation Dataset for Recommender Systems
ArticleAbstract: The existing scientific documentation-based recommender systems focus on exploiting the citations anPalabras claves:Artificial Intelligence, Data Mining, Dataset, Machine learning, recommender systems, Scientific documentation, SCOPUS, TopicsAutores:Bobadilla J., Gutiérrez A., Li X., Ortega F., Remigio Hurtado OrtizFuentes:googlescopusHybrid Collaborative Filtering Based on Users Rating Behavior
ArticleAbstract: Several collaborative filtering (CF) approaches have been developed in order to improve the qualityPalabras claves:COLLABORATIVE FILTERING, hybrid CF, Knn, matrix factorization, recommender systemsAutores:Ortega F., Priscila Valdiviezo-Diaz, Raya L., Rojo D.Fuentes:googlescopusRecommendation to Groups of Users Using the Singularities Concept
ArticleAbstract: Recommendation to a group of users is a big challenge for collaborative filtering. The recommendatioPalabras claves:COLLABORATIVE FILTERING, group of users, Recommendation to groups, recommender systems, SingularityAutores:Bobadilla J., Ortega F., Remigio Hurtado Ortiz, Rodolfo Bojorque-ChasiFuentes:googlescopus