45 citations · 147 across the 11 of their papers we have counts for
4 papers · 1 filter
Deep Neural Aggregation for Recommending Items to Group of Users
Jorge Dueñas-Lerín, Raúl Lara-Cabrera, Fernando Ortega +1
Modern society devotes a significant amount of time to digital interaction. Many of our daily actions are carried out through digital means. This has led to the emergence of numero…
Neural Group Recommendation Based on a Probabilistic Semantic Aggregation
Jorge Dueñas-Lerín, Raúl Lara-Cabrera, Fernando Ortega +1
Recommendation to groups of users is a challenging subfield of recommendation systems. Its key concept is how and where to make the aggregation of each set of user information into…
Restricted Bernoulli Matrix Factorization: Balancing the trade-off between prediction accuracy and coverage in classification based collaborative filtering
Ángel 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…
Deep Learning feature selection to unhide demographic recommender systems factors
Jesús Bobadilla, Ángel González-Prieto, Fernando Ortega +1
Extracting demographic features from hidden factors is an innovative concept that provides multiple and relevant applications. The matrix factorization model generates factors whic…