49 citations · 227 across the 12 of their papers we have counts for
5 papers · 1 filter
Comprehensive Evaluation of Matrix Factorization Models for Collaborative Filtering Recommender Systems
Jesús Bobadilla, Jorge Dueñas-Lerín, 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…
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…
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…
Reliability quality measures for recommender systems
Jesús Bobadilla, Abraham Gutierrez, Fernando Ortega +1
Users want to know the reliability of the recommendations; they do not accept high predictions if there is no reliability evidence. Recommender systems should provide reliability v…
CF4J: Collaborative Filtering for Java
Fernando Ortega, Bo Zhu, Jesus Bobadilla +1
Recommender Systems (RS) provide a relevant tool to mitigate the information overload problem. A large number of researchers have published hundreds of papers to improve different…