3 papers
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
Testing Deep Learning Recommender Systems Models on Synthetic GAN-Generated Datasets
Jesús Bobadilla, Abraham Gutiérrez
The published method Generative Adversarial Networks for Recommender Systems (GANRS) allows generating data sets for collaborative filtering recommendation systems. The GANRS sourc…
cs.IR2024
Neural Collaborative Filtering Classification Model to Obtain Prediction Reliabilities
Jesús Bobadilla, Abraham Gutiérrez, Santiago Alonso +1
Neural collaborative filtering is the state of art field in the recommender systems area; it provides some models that obtain accurate predictions and recommendations. These models…