3 papers
cs.IR2026
Restricted Bernoulli Matrix Factorization: Balancing the trade-off between prediction accuracy and coverage in classification based collaborative filtering
Ãngel González-Prieto, Abraham Gutiérrez, Fernando Ortega +1
Reliability measures associated with the prediction of the machine learning models are critical to strengthening user confidence in artificial intelligence. Therefore, those models…
cs.IR2024
Comprehensive Evaluation of Matrix Factorization Models for Collaborative Filtering Recommender Systems
Jesús Bobadilla, Jorge Dueñas-LerÃn, Fernando Ortega +1
Matrix factorization models are the core of current commercial collaborative filtering Recommender Systems. This paper tested six representative matrix factorization models, using…
cs.IR2024
Incorporating Recklessness to Collaborative Filtering based Recommender Systems
Diego Pérez-López, Fernando Ortega, Ãngel González-Prieto +1
Recommender systems are intrinsically tied to a reliability/coverage dilemma: The more reliable we desire the forecasts, the more conservative the decision will be and thus, the fe…