3 papers
cs.IR2021
Deep Variational Models for Collaborative Filtering-based Recommender Systems
Jesús Bobadilla, Fernando Ortega, Abraham Gutiérrez +1
Deep learning provides accurate collaborative filtering models to improve recommender system results. Deep matrix factorization and their related collaborative neural networks are…
cs.IR2020
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…
cs.LG2020
DeepFair: Deep Learning for Improving Fairness in Recommender Systems
Jesús Bobadilla, Raúl Lara-Cabrera, Ángel González-Prieto +1
The lack of bias management in Recommender Systems leads to minority groups receiving unfair recommendations. Moreover, the trade-off between equity and precision makes it difficul…