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A comparative analysis of similarity metrics on sparse data for clustering in recommender systems
Conference ObjectAbstract: This work shows similarity metrics behavior on sparse data for recommender systems (RS). ClusteringPalabras claves:clustering, recommender systems, Similarity MeasuresAutores:César Inga Chalco, Remigio Hurtado Ortiz, Rodolfo Bojorque-ChasiFuentes: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:googlescopusAn 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, prediction time, recommender systems, Similarity MeasuresAutores:Bobadilla J., Ortega F., Remigio Hurtado Ortiz, Zhu B.Fuentes:googlescopusHierarchical clustering for collaborative filtering recommender systems
Conference ObjectAbstract: Nowadays, the Recommender Systems (RS) that use Collaborative Filtering (CF) are objects of interestPalabras claves:Agglomerative hierarchical clustering, COLLABORATIVE FILTERING, recommender systems, Similarity metricsAutores:César Inga Chalco, Remigio Hurtado Ortiz, Rodolfo Bojorque-ChasiFuentes: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:googlescopusMatrix Factorization-Based Clustering for Sparse Data in Recommender Systems: A Comparative Study
ArticleAbstract: Clustering techniques significantly enhance recommender systems by improving predictive accuracy andPalabras claves:clustering, matrix factorization, recommender systemsAutores:Remigio Hurtado Ortiz, Rodolfo Bojorque-ChasiFuentes:scopusA collaborative filtering probabilistic approach for recommendation to large homogeneous and automatically detected groups
ArticleAbstract: In the collaborative filtering recommender systems (CFRS) field, recommendation to group of users isPalabras claves:Collaborative Filtering Clustering, Dimensionality reduction, group recommendation, Homogenous Groups, recommender systemsAutores:Alonso S., Bobadilla J., Gutiérrez A., Remigio Hurtado OrtizFuentes:scopusA Categorical Transformer with a Data Science Approach for Recommendation Systems Based on Collaborative Filtering
OtherAbstract: Recommender systems help predict what customers might like, such as movies, restaurants, or productsPalabras claves:Categorical transformer, COLLABORATIVE FILTERING, data science, Data transformation, Machine Learning, recommender systemsAutores:Arantxa Muñoz, Remigio Hurtado OrtizFuentes:scopus