49 citations · 97 across the 4 of their papers we have counts for
4 papers
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…
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…
Creating Synthetic Datasets for Collaborative Filtering Recommender Systems using Generative Adversarial Networks
Jesús Bobadilla, Abraham Gutiérrez, Raciel Yera +1
Research and education in machine learning needs diverse, representative, and open datasets that contain sufficient samples to handle the necessary training, validation, and testin…