Fernando Ortega

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 46

Top Topics

Comprehensive Evaluation

Recommender Systems

Top Venues

Knowl. Based Syst.

Publications

Jesús Bobadilla, Abraham Gutiérrez, Fernando Ortega, Bo Zhu
Reliability quality measures for recommender systems. CoRR (2024)
Diego Pérez-López, Fernando Ortega, Ángel González-Prieto, Jorge Dueñas-Lerín
Incorporating recklessness to collaborative filtering based recommender systems. Inf. Sci. 679 (2024)
Jesús Bobadilla, Jorge Dueñas-Lerín, Fernando Ortega, Abraham Gutiérrez
Comprehensive Evaluation of Matrix Factorization Models for Collaborative Filtering Recommender Systems. Int. J. Interact. Multim. Artif. Intell. 8 (6) (2024)
Fernando Ortega, Bo Zhu, Jesús Bobadilla, Antonio Hernando
CF4J: Collaborative Filtering for Java. CoRR (2024)
Jorge Dueñas-Lerín, Raúl Lara-Cabrera, Fernando Ortega, Jesús Bobadilla
Neural Group Recommendation Based on a Probabilistic Semantic Aggregation. CoRR (2023)
Jesús Bobadilla, Fernando Ortega, Abraham Gutiérrez, Ángel González-Prieto
Deep variational models for collaborative filtering-based recommender systems. Neural Comput. Appl. 35 (10) (2023)
Diego Pérez-López, Fernando Ortega, Ángel González-Prieto, Jorge Dueñas-Lerín
Incorporating Recklessness to Collaborative Filtering based Recommender Systems. CoRR (2023)
Raúl Lara-Cabrera, Ángel González-Prieto, Diego Pérez-López, Diego Trujillo, Fernando Ortega
An evaluation framework for dimensionality reduction through sectional curvature. CoRR (2023)
Raúl Lara-Cabrera, Fernando Ortega, Edgar Talavera, Daniel López-Fernández
Using 3D printed badges to improve student performance and reduce dropout rates in STEM higher education. CoRR (2023)
Jorge Dueñas-Lerín, Raúl Lara-Cabrera, Fernando Ortega, Jesús Bobadilla
Deep Neural Aggregation for Recommending Items to Group of Users. CoRR (2023)
Jorge Dueñas-Lerín, Raúl Lara-Cabrera, Fernando Ortega, Jesús Bobadilla
Neural group recommendation based on a probabilistic semantic aggregation. Neural Comput. Appl. 35 (19) (2023)
Raúl Lara-Cabrera, Fernando Ortega, Edgar Talavera, Daniel López-Fernández
Using 3-D Printed Badges to Improve Student Performance and Reduce Dropout Rates in STEM Higher Education. IEEE Trans. Educ. 66 (6) (2023)
Álvaro González, Fernando Ortega, Diego Pérez-López, Santiago Alonso
Bias and Unfairness of Collaborative Filtering Based Recommender Systems in MovieLens Dataset. IEEE Access 10 (2022)
Jesús Bobadilla, Ángel González-Prieto, Fernando Ortega, Raúl Lara-Cabrera
Deep learning approach to obtain collaborative filtering neighborhoods. Neural Comput. Appl. 34 (4) (2022)
Ángel González-Prieto, Abraham Gutiérrez, Fernando Ortega, Raúl Lara-Cabrera
ResBeMF: Improving Prediction Coverage of Classification based Collaborative Filtering. CoRR (2022)
Fernando Ortega, Jesús Mayor, Daniel López-Fernández, Raúl Lara-Cabrera
CF4J 2.0: Adapting Collaborative Filtering for Java to new challenges of collaborative filtering based recommender systems. Knowl. Based Syst. 215 (2021)
Daniel López-Fernández, Aldo Gordillo, Fernando Ortega, Agustín Yagüe, Edmundo Tovar
LEGO® Serious Play in Software Engineering Education. IEEE Access 9 (2021)
Jesús Bobadilla, Ángel González-Prieto, Fernando Ortega, Raúl Lara-Cabrera
Deep learning feature selection to unhide demographic recommender systems factors. Neural Comput. Appl. 33 (12) (2021)
Jesús Bobadilla, Raúl Lara-Cabrera, Ángel González-Prieto, Fernando Ortega
DeepFair: Deep Learning for Improving Fairness in Recommender Systems. Int. J. Interact. Multim. Artif. Intell. 6 (6) (2021)
Fernando Ortega, Raúl Lara-Cabrera, Ángel González-Prieto, Jesús Bobadilla
Providing reliability in recommender systems through Bernoulli Matrix Factorization. Inf. Sci. 553 (2021)
Jesús Bobadilla, Fernando Ortega, Abraham Gutiérrez, Ángel González-Prieto
Deep Variational Models for Collaborative Filtering-based Recommender Systems. CoRR (2021)
Jesús Bobadilla, Fernando Ortega, Abraham Gutiérrez, Santiago Alonso
Classification-based Deep Neural Network Architecture for Collaborative Filtering Recommender Systems. Int. J. Interact. Multim. Artif. Intell. 6 (1) (2020)
Fernando Ortega, Raúl Lara-Cabrera, Ángel González-Prieto, Jesús Bobadilla
Providing reliability in Recommender Systems through Bernoulli Matrix Factorization. CoRR (2020)
Francisco Pajuelo-Holguera, Juan Antonio Gómez Pulido, Fernando Ortega, José M. Granado Criado
Recommender system implementations for embedded collaborative filtering applications. Microprocess. Microsystems 73 (2020)
Fernando Ortega, Ángel González-Prieto, Jesús Bobadilla, Abraham Gutiérrez
Collaborative Filtering to Predict Sensor Array Values in Large IoT Networks. Sensors 20 (16) (2020)
Francisco Pajuelo-Holguera, Juan Antonio Gómez Pulido, Fernando Ortega
Recommender systems for sensor-based ambient control in academic facilities. Eng. Appl. Artif. Intell. 96 (2020)
Jesús Bobadilla, Raúl Lara-Cabrera, Ángel González-Prieto, Fernando Ortega
DeepFair: Deep Learning for Improving Fairness in Recommender Systems. CoRR (2020)
Jesús Mayor, Raúl Lara-Cabrera, Daniel López-Fernández, Fernando Ortega
Entornos parcialmente no euclidianos en realidad virtual(Partially non-Euclidean environments in virtual reality). CoSECivi (2020)
Jesús Bobadilla, Ángel González-Prieto, Fernando Ortega, Raúl Lara-Cabrera
Deep Learning feature selection to unhide demographic recommender systems factors. CoRR (2020)
Santiago Alonso, Jesús Bobadilla, Fernando Ortega, Ricardo Moya
Robust Model-Based Reliability Approach to Tackle Shilling Attacks in Collaborative Filtering Recommender Systems. IEEE Access 7 (2019)
Priscila Valdiviezo, Fernando Ortega, Eduardo Cobos, Raúl Lara-Cabrera
A Collaborative Filtering Approach Based on Naïve Bayes Classifier. IEEE Access 7 (2019)
Remigio Hurtado, Jesús Bobadilla, Rodolfo Bojorque, Fernando Ortega, Xin Li
A New Recommendation Approach Based on Probabilistic Soft Clustering Methods: A Scientific Documentation Case Study. IEEE Access 7 (2019)
Daniel López-Fernández, Edmundo Tovar, Pedro Pablo Alarcón, Fernando Ortega
Motivation of Computer Science Engineering Students: Analysis and Recommendations. FIE (2019)
Francisco Pajuelo-Holguera, Juan Antonio Gómez Pulido, Fernando Ortega
Evaluating Strategies for Selecting Test Datasets in Recommender Systems. HAIS (2019)
Fernando Ortega, Bo Zhu, Jesús Bobadilla, Antonio Hernando
CF4J: Collaborative filtering for Java. Knowl. Based Syst. 152 (2018)
S. Gil, Jesús Bobadilla, Fernando Ortega, Bo Zhu
: Java framework for visualization of recommender systems information. Knowl. Based Syst. 155 (2018)
Fernando Ortega, Remigio Hurtado, Jesús Bobadilla, Rodolfo Bojorque
Recommendation to Groups of Users Using the Singularities Concept. IEEE Access 6 (2018)
Bo Zhu, Fernando Ortega, Jesús Bobadilla, Abraham Gutiérrez
Assigning reliability values to recommendations using matrix factorization. J. Comput. Sci. 26 (2018)
Jesús Bobadilla, Abraham Gutiérrez, Fernando Ortega, Bo Zhu
Reliability quality measures for recommender systems. Inf. Sci. (2018)
Antonio Hernando, Jesús Bobadilla, Fernando Ortega, Abraham Gutiérrez
Method to interactively visualize and navigate related information. Expert Syst. Appl. 111 (2018)
Fernando Ortega, Jesús Bobadilla, Abraham Gutiérrez, Remigio Hurtado, Xin Li
Artificial Intelligence Scientific Documentation Dataset for Recommender Systems. IEEE Access 6 (2018)
Fernando Ortega, Diego Rojo, Priscila Valdiviezo, Laura Raya
Hybrid Collaborative Filtering Based on Users Rating Behavior. IEEE Access 6 (2018)
Bo Zhu, Remigio Hurtado, Jesús Bobadilla, Fernando Ortega
An Efficient Recommender System Method Based on the Numerical Relevances and the Non-Numerical Structures of the Ratings. IEEE Access 6 (2018)
Antonio Hernando, Jesús Bobadilla, Fernando Ortega, Abraham Gutiérrez
A probabilistic model for recommending to new cold-start non-registered users. Inf. Sci. 376 (2017)
Antonio Hernando, Jesús Bobadilla, Fernando Ortega
A non negative matrix factorization for collaborative filtering recommender systems based on a Bayesian probabilistic model. Knowl. Based Syst. 97 (2016)
Fernando Ortega, Antonio Hernando, Jesús Bobadilla, Jeon-Hyung Kang
Recommending items to group of users using Matrix Factorization based Collaborative Filtering. Inf. Sci. 345 (2016)
Fernando Ortega, Jesús Bobadilla, Antonio Hernando, Fernando Rodríguez
Using Hierarchical Graph Maps to Explain Collaborative Filtering Recommendations. Int. J. Intell. Syst. 29 (5) (2014)
Antonio Hernando, Ricardo Moya, Fernando Ortega, Jesús Bobadilla
Hierarchical graph maps for visualization of collaborative recommender systems. J. Inf. Sci. 40 (1) (2014)
Antonio Hernando, Jesús Bobadilla, Fernando Ortega, Jorge Tejedor
Incorporating reliability measurements into the predictions of a recommender system. Inf. Sci. 218 (2013)
Antonio Hernando, Jesús Bobadilla, Fernando Ortega, Abraham Gutiérrez
Trees for explaining recommendations made through collaborative filtering. Inf. Sci. 239 (2013)
Fernando Ortega, Jesús Bobadilla, Antonio Hernando, Abraham Gutiérrez
Incorporating group recommendations to recommender systems: Alternatives and performance. Inf. Process. Manag. 49 (4) (2013)
Jesús Bobadilla, Fernando Ortega, Antonio Hernando, Abraham Gutiérrez
Recommender systems survey. Knowl. Based Syst. 46 (2013)
Fernando Ortega, José Luis Sánchez, Jesús Bobadilla, Abraham Gutiérrez
Improving collaborative filtering-based recommender systems results using Pareto dominance. Inf. Sci. 239 (2013)
Jesús Bobadilla, Fernando Ortega, Antonio Hernando, Guillermo Glez. de Rivera
A similarity metric designed to speed up, using hardware, the recommender systems k-nearest neighbors algorithm. Knowl. Based Syst. 51 (2013)
Jesús Bobadilla, Fernando Ortega, Antonio Hernando, Angel Arroyo
A balanced memory-based collaborative filtering similarity measure. Int. J. Intell. Syst. 27 (10) (2012)
Jesús Bobadilla, Fernando Ortega, Antonio Hernando
A collaborative filtering similarity measure based on singularities. Inf. Process. Manag. 48 (2) (2012)
Jesús Bobadilla, Fernando Ortega, Antonio Hernando, Jesus Bernal
Generalization of recommender systems: Collaborative filtering extended to groups of users and restricted to groups of items. Expert Syst. Appl. 39 (1) (2012)
Jesús Bobadilla, Fernando Ortega, Antonio Hernando, Jesus Bernal
A collaborative filtering approach to mitigate the new user cold start problem. Knowl. Based Syst. 26 (2012)
Jesús Bobadilla, Antonio Hernando, Fernando Ortega, Abraham Gutiérrez
Collaborative filtering based on significances. Inf. Sci. 185 (1) (2012)
Jesús Bobadilla, Antonio Hernando, Fernando Ortega, Jesus Bernal
A framework for collaborative filtering recommender systems. Expert Syst. Appl. 38 (12) (2011)
Fernando Ortega, Antonio Hernando, Jesús Bobadilla
Extended Precision Quality Measure for Recommender Systems. CAEPIA (2011)
Jesús Bobadilla, Fernando Ortega, Antonio Hernando, Javier Alcalá
Improving collaborative filtering recommender system results and performance using genetic algorithms. Knowl. Based Syst. 24 (8) (2011)