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2019 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2019(2)
2022 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2022(1)
Advances in Intelligent Systems and Computing(1)
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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:googlescopusA 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 approach hybrid recommender system of item bundles for group of users
Conference ObjectAbstract: User recommendation is a big challenge for collaborative filtering, due to the large number of usersPalabras claves:Autores:Bryam Vega Moreno, David Andres Morales Rivera, Remigio Hurtado OrtizFuentes:scopusA 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:googlescopusA new way of finding better neighbors in recommendation systems based on collaborative filtering
Conference ObjectAbstract: One of the biggest problems of the internet is information overload. A way to handle this is CollaboPalabras claves:Autores:Alejandro Sebastian Enriquez Mancheno, Domenica Alejandra Merchan Garcia, Remigio Hurtado OrtizFuentes:googlescopusData Analysis Architecture using Techniques of Machine Learning for the Pbkp_rediction of the Quality of Blood Fonations against the Hepatitis C Virus
Conference ObjectAbstract: Nowadays the WHO (World health Organization) has difficulties improving the access to safe blood. ThPalabras claves:Artificial Neural Network, Blood Donor, data science, HEPATITIS C, K-Nearest-Neighbor, Machine learning, neural network, Oversizing, Principal Component Analysis, random forest, Support Vector MachineAutores:Denys Dutan-Sanchez, Paul Idrovo, Paul Idrovo-Berrezueta, Remigio Hurtado Ortiz, Vladimir Robles-BykbaevFuentes: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