• Classification-based Deep Neural Network Architecture for Collaborative Filtering Recommender Systems 

      Bobadilla, Jesús; Ortega, Fernando; Gutiérrez, Abraham; Alonso, Santiago (International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI), 03/2020)
      This paper proposes a scalable and original classification-based deep neural architecture. Its collaborative filtering approach can be generalized to most of the existing recommender systems, since it just operates on the ...
    • Comprehensive Evaluation of Matrix Factorization Models for Collaborative Filtering Recommender Systems 

      Bobadilla, Jesús; Dueñas-Lerín, Jorge; Ortega, Fernando; Gutiérrez, Abraham (International Journal of Interactive Multimedia and Artificial Intelligence, 04/2023)
      Matrix factorization models are the core of current commercial collaborative filtering Recommender Systems. This paper tested six representative matrix factorization models, using four collaborative filtering datasets. ...
    • DeepFair: Deep Learning for Improving Fairness in Recommender Systems 

      Bobadilla, Jesús; Lara-Cabrera, Raúl; González-Prieto, Ángel; Ortega, Fernando (International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI), 06/2021)
      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 difficult to obtain recommendations that meet both ...