Mostrando 7 resultados de: 7
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IEEE Access(5)
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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:googlescopusAnalysis of scientific production based on trending research topics. An Artificial Intelligence case study
ArticleAbstract: Scientific documentation research leads to the computation of large amounts of information from publPalabras claves:Artificial intelligence trends, Data Mining, Machine learning, Natural Language processing, Research topics, Scientific documentation, Scientific production, SCOPUSAutores:Bobadilla J., Gutiérrez A., Patricio M.Á., Rodolfo Bojorque-ChasiFuentes:googlescopusA hybrid approach of recommendation via extended matrix based on collaborative filtering with demographics information
Conference ObjectAbstract: In view of the growth in the use of methods based on matrix factorization, this research proposes anPalabras claves:COLLABORATIVE FILTERING, Demographic information, Extended matrix, matrix factorization, Recommender system, Sparse dataAutores:Bobadilla J., Priscila Valdiviezo-DiazFuentes:googlescopusA new recommendation approach based on probabilistic soft clustering methods: A scientific documentation case study
ArticleAbstract: Recommender system (RS) clustering is an important issue, both for the improvement of the collaboratPalabras claves:COLLABORATIVE FILTERING, recommender systems, Scientific documentation, Soft clusteringAutores:Bobadilla J., Li X., Ortega F., Remigio Hurtado Ortiz, Rodolfo Bojorque-ChasiFuentes: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: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:googlescopusRecommender systems clustering using Bayesian non negative matrix factorization
ArticleAbstract: Recommender Systems present a high-level of sparsity in their ratings matrices. The collaborative fiPalabras claves:Bayesian NMF, COLLABORATIVE FILTERING, Hard clustering, matrix factorization, Pre-clustering, recommender systems, Sparse dataAutores:Bobadilla J., Hernando A., Remigio Hurtado Ortiz, Rodolfo Bojorque-ChasiFuentes:googlescopus