Extended Precision Quality Measure for Recommender Systems. - Fernando Ortega 001; Antonio Hernando; Jesús Bobadilla (CAEPIA, 2011)

A framework for collaborative filtering recommender systems. - Jesús Bobadilla; Antonio Hernando; Fernando Ortega 001; Jesus Bernal (Expert Syst. Appl., 2011)

Improving collaborative filtering recommender system results and performance using genetic algorithms. - Jesús Bobadilla; Fernando Ortega 001; Antonio Hernando; Javier Alcalá (Knowl. Based Syst., 2011)

Generalization of recommender systems: Collaborative filtering extended to groups of users and restricted to groups of items. - Jesús Bobadilla; Fernando Ortega 001; Antonio Hernando; Jesus Bernal (Expert Syst. Appl., 2012)

A balanced memory-based collaborative filtering similarity measure. - Jesús Bobadilla; Fernando Ortega 001; Antonio Hernando; Angel Arroyo (Int. J. Intell. Syst., 2012)

A collaborative filtering similarity measure based on singularities. - Jesús Bobadilla; Fernando Ortega 001; Antonio Hernando (Inf. Process. Manag., 2012)

Collaborative filtering based on significances. - Jesús Bobadilla; Antonio Hernando; Fernando Ortega 001; Abraham Gutiérrez (Inf. Sci., 2012)

A collaborative filtering approach to mitigate the new user cold start problem. - Jesús Bobadilla; Fernando Ortega 001; Antonio Hernando; Jesus Bernal (Knowl. Based Syst., 2012)

Incorporating group recommendations to recommender systems: Alternatives and performance. - Fernando Ortega 001; Jesús Bobadilla; Antonio Hernando; Abraham Gutiérrez (Inf. Process. Manag., 2013)

Trees for explaining recommendations made through collaborative filtering. - Antonio Hernando; Jesús Bobadilla; Fernando Ortega 001; Abraham Gutiérrez (Inf. Sci., 2013)

Incorporating reliability measurements into the predictions of a recommender system. - Antonio Hernando; Jesús Bobadilla; Fernando Ortega 001; Jorge Tejedor (Inf. Sci., 2013)

Improving collaborative filtering-based recommender systems results using Pareto dominance. - Fernando Ortega 001; José Luis Sánchez; Jesús Bobadilla; Abraham Gutiérrez (Inf. Sci., 2013)

Recommender systems survey. - Jesús Bobadilla; Fernando Ortega 001; Antonio Hernando; Abraham Gutiérrez (Knowl. Based Syst., 2013)

A similarity metric designed to speed up, using hardware, the recommender systems k-nearest neighbors algorithm. - Jesús Bobadilla; Fernando Ortega 001; Antonio Hernando; Guillermo Glez. de Rivera (Knowl. Based Syst., 2013)

Using Hierarchical Graph Maps to Explain Collaborative Filtering Recommendations. - Fernando Ortega 001; Jesús Bobadilla; Antonio Hernando; Fernando Rodríguez (Int. J. Intell. Syst., 2014)

Hierarchical graph maps for visualization of collaborative recommender systems. - Antonio Hernando; Ricardo Moya; Fernando Ortega 001; Jesús Bobadilla (J. Inf. Sci., 2014)

Incorporating Group Recommendations to Recommender Systems: Alternatives and Performance. - Fernando Ortega Requena (2015)

Recommending items to group of users using Matrix Factorization based Collaborative Filtering. - Fernando Ortega 001; Antonio Hernando; Jesús Bobadilla; Jeon-Hyung Kang (Inf. Sci., 2016)

A non negative matrix factorization for collaborative filtering recommender systems based on a Bayesian probabilistic model. - Antonio Hernando; Jesús Bobadilla; Fernando Ortega 001 (Knowl. Based Syst., 2016)

A probabilistic model for recommending to new cold-start non-registered users. - Antonio Hernando; Jesús Bobadilla; Fernando Ortega 001; Abraham Gutiérrez (Inf. Sci., 2017)

Artificial Intelligence Scientific Documentation Dataset for Recommender Systems. - Fernando Ortega 001; Jesús Bobadilla; Abraham Gutiérrez; Remigio Hurtado; Xin Li 033 (IEEE Access, 2018)

Recommendation to Groups of Users Using the Singularities Concept. - Fernando Ortega 001; Remigio Hurtado; Jesús Bobadilla; Rodolfo Bojorque (IEEE Access, 2018)

Hybrid Collaborative Filtering Based on Users Rating Behavior. - Fernando Ortega 001; Diego Rojo; Priscila Valdiviezo; Laura Raya (IEEE Access, 2018)

An Efficient Recommender System Method Based on the Numerical Relevances and the Non-Numerical Structures of the Ratings. - Bo Zhu 008; Remigio Hurtado; Jesús Bobadilla; Fernando Ortega 001 (IEEE Access, 2018)

Method to interactively visualize and navigate related information. - Antonio Hernando; Jesús Bobadilla; Fernando Ortega 001; Abraham Gutiérrez (Expert Syst. Appl., 2018)

Reliability quality measures for recommender systems. - Jesús Bobadilla; Abraham Gutiérrez; Fernando Ortega 001; Bo Zhu 008 (Inf. Sci., 2018)

Assigning reliability values to recommendations using matrix factorization. - Bo Zhu 008; Fernando Ortega 001; Jesús Bobadilla; Abraham Gutiérrez (J. Comput. Sci., 2018)

VisualRS: Java framework for visualization of recommender systems information. - S. Gil; Jesús Bobadilla; Fernando Ortega 001; Bo Zhu 008 (Knowl. Based Syst., 2018)

CF4J: Collaborative filtering for Java. - Fernando Ortega 001; Bo Zhu 008; Jesús Bobadilla; Antonio Hernando (Knowl. Based Syst., 2018)

Motivation of Computer Science Engineering Students: Analysis and Recommendations. - Daniel López-Fernández; Edmundo Tovar; Pedro Pablo Alarcón; Fernando Ortega 001 (FIE, 2019)

Evaluating Strategies for Selecting Test Datasets in Recommender Systems. - Francisco Pajuelo-Holguera; Juan Antonio Gómez Pulido; Fernando Ortega 001 (HAIS, 2019)

Robust Model-Based Reliability Approach to Tackle Shilling Attacks in Collaborative Filtering Recommender Systems. - Santiago Alonso; Jesús Bobadilla; Fernando Ortega 001; Ricardo Moya (IEEE Access, 2019)

A New Recommendation Approach Based on Probabilistic Soft Clustering Methods: A Scientific Documentation Case Study. - Remigio Hurtado; Jesús Bobadilla; Rodolfo Bojorque; Fernando Ortega 001; Xin Li 033 (IEEE Access, 2019)

A Collaborative Filtering Approach Based on Naïve Bayes Classifier. - Priscila Valdiviezo; Fernando Ortega 001; Eduardo Cobos; Raúl Lara-Cabrera (IEEE Access, 2019)

MaliciousML: MovieLens dataset attacked with diverse profile injection attacks. - Santiago Alonso; Jesús Bobadilla; Fernando Ortega 001; Ricardo Moya (IEEE DataPort, 2019)

Entornos parcialmente no euclidianos en realidad virtual(Partially non-Euclidean environments in virtual reality). - Jesús Mayor; Raúl Lara-Cabrera; Daniel López-Fernández; Fernando Ortega 001 (CoSECivi, 2020)

Recommender systems for sensor-based ambient control in academic facilities. - Francisco Pajuelo-Holguera; Juan Antonio Gómez Pulido; Fernando Ortega 001 (Eng. Appl. Artif. Intell., 2020)

Classification-based Deep Neural Network Architecture for Collaborative Filtering Recommender Systems. - Jesús Bobadilla; Fernando Ortega 001; Abraham Gutiérrez; Santiago Alonso (Int. J. Interact. Multim. Artif. Intell., 2020)

Recommender system implementations for embedded collaborative filtering applications. - Francisco Pajuelo-Holguera; Juan Antonio Gómez Pulido; Fernando Ortega 001; José M. Granado Criado (Microprocess. Microsystems, 2020)

Collaborative Filtering to Predict Sensor Array Values in Large IoT Networks. - Fernando Ortega 001; Ángel González-Prieto; Jesús Bobadilla; Abraham Gutiérrez (Sensors, 2020)

LEGO® Serious Play in Software Engineering Education. - Daniel López-Fernández; Aldo Gordillo; Fernando Ortega 001; Agustín Yagüe; Edmundo Tovar (IEEE Access, 2021)

DeepFair: Deep Learning for Improving Fairness in Recommender Systems. - Jesús Bobadilla; Raúl Lara-Cabrera; Ángel González-Prieto; Fernando Ortega 001 (Int. J. Interact. Multim. Artif. Intell., 2021)

Providing reliability in recommender systems through Bernoulli Matrix Factorization. - Fernando Ortega 001; Raúl Lara-Cabrera; Ángel González-Prieto; Jesús Bobadilla (Inf. Sci., 2021)

CF4J 2.0: Adapting Collaborative Filtering for Java to new challenges of collaborative filtering based recommender systems. - Fernando Ortega 001; Jesús Mayor; Daniel López-Fernández; Raúl Lara-Cabrera (Knowl. Based Syst., 2021)

Deep learning feature selection to unhide demographic recommender systems factors. - Jesús Bobadilla; Ángel González-Prieto; Fernando Ortega 001; Raúl Lara-Cabrera (Neural Comput. Appl., 2021)

Bias and Unfairness of Collaborative Filtering Based Recommender Systems in MovieLens Dataset. - Álvaro González; Fernando Ortega 001; Diego Pérez-López; Santiago Alonso (IEEE Access, 2022)

ResBeMF: Improving Prediction Coverage of Classification based Collaborative Filtering. - Ángel González-Prieto; Abraham Gutiérrez; Fernando Ortega 001; Raúl Lara-Cabrera (CoRR, 2022)

Deep learning approach to obtain collaborative filtering neighborhoods. - Jesús Bobadilla; Ángel González-Prieto; Fernando Ortega 001; Raúl Lara-Cabrera (Neural Comput. Appl., 2022)

Using 3D printed badges to improve student performance and reduce dropout rates in STEM higher education. - Raúl Lara-Cabrera; Fernando Ortega 001; Edgar Talavera; Daniel López-Fernández (CoRR, 2023)

An evaluation framework for dimensionality reduction through sectional curvature. - Raúl Lara-Cabrera; Ángel González-Prieto; Diego Pérez-López; Diego Trujillo; Fernando Ortega 001 (CoRR, 2023)

Deep variational models for collaborative filtering-based recommender systems. - Jesús Bobadilla; Fernando Ortega 001; Abraham Gutiérrez; Ángel González-Prieto (Neural Comput. Appl., 2023)

Neural group recommendation based on a probabilistic semantic aggregation. - Jorge Dueñas-Lerín; Raúl Lara-Cabrera; Fernando Ortega 001; Jesús Bobadilla (Neural Comput. Appl., 2023)

Using 3-D Printed Badges to Improve Student Performance and Reduce Dropout Rates in STEM Higher Education. - Raúl Lara-Cabrera; Fernando Ortega 001; Edgar Talavera; Daniel López-Fernández (IEEE Trans. Educ., 2023)

Comprehensive Evaluation of Matrix Factorization Models for Collaborative Filtering Recommender Systems. - Jesús Bobadilla; Jorge Dueñas-Lerín; Fernando Ortega 001; Abraham Gutiérrez (Int. J. Interact. Multim. Artif. Intell., 2024)

Incorporating recklessness to collaborative filtering based recommender systems. - Diego Pérez-López; Fernando Ortega 001; Ángel González-Prieto; Jorge Dueñas-Lerín (Inf. Sci., 2024)

Deep neural aggregation for recommending items to group of users. - Jorge Dueñas-Lerín; Raúl Lara-Cabrera; Fernando Ortega 001; Jesús Bobadilla (Appl. Soft Comput., 2025)