Ángel González-Prieto

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 33

Top Topics

Dimensionality Reduction

Matrix Factorization

Collaborative Filtering

Top Venues

Neural Comput. Appl.

J. Syst. Softw.

Publications

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, Fernando Ortega, Abraham Gutiérrez, Ángel González-Prieto
Deep variational models for collaborative filtering-based recommender systems. Neural Comput. Appl. 35 (10) (2023)
Guillermo Iglesias, Edgar Talavera, Ángel González-Prieto, Alberto Mozo, Sandra Gómez Canaval
Data Augmentation techniques in time series domain: a survey and taxonomy. Neural Comput. Appl. 35 (14) (2023)
Diego Pérez-López, Fernando Ortega, Ángel González-Prieto, Jorge Dueñas-Lerín
Incorporating Recklessness to Collaborative Filtering based Recommender Systems. CoRR (2023)
Jessica Díaz, Jorge Pérez, Carolina Gallardo, Ángel González-Prieto
Applying Inter-Rater Reliability and Agreement in collaborative Grounded Theory studies in software engineering. J. Syst. Softw. 195 (2023)
Ángel González-Prieto, Jorge Pérez, Jessica Díaz, Daniel López-Fernández
Reliability in software engineering qualitative research through Inter-Coder Agreement. J. Syst. Softw. 202 (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)
Ángel González-Prieto, Antonio Brú, Juan Carlos Nuño, José Luis González-Álvarez
Hybrid machine learning methods for risk assessment in gender-based crime. Knowl. Based Syst. 260 (2023)
Ángel González-Prieto, Alberto Mozo, Sandra Gómez Canaval, Edgar Talavera
Improving the quality of generative models through Smirnov transformation. Inf. Sci. 609 (2022)
Jorge Pérez, Ángel González-Prieto, Jessica Díaz, Daniel López-Fernández, Javier García Martin, Agustín Yagüe
DevOps Research-Based Teaching Using Qualitative Research and Inter-Coder Agreement. IEEE Trans. Software Eng. 48 (9) (2022)
Edgar Talavera, Guillermo Iglesias, Ángel González-Prieto, Alberto Mozo, Sandra Gómez Canaval
Data Augmentation techniques in time series domain: A survey and taxonomy. CoRR (2022)
Daniel López-Fernández, Jessica Díaz, Javier Garcia, Jorge Pérez, Ángel González-Prieto
DevOps Team Structures: Characterization and Implications. IEEE Trans. Software Eng. 48 (10) (2022)
Jorge Pérez, Jessica Díaz, Javier Berrocal, Ramón López-Viana, Ángel González-Prieto
Edge computing. Computing 104 (12) (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, Alberto Mozo, Edgar Talavera, Sandra Gómez Canaval
Dynamics of Fourier Modes in Torus Generative Adversarial Networks. CoRR (2022)
Jesús Bobadilla, Abraham Gutiérrez, Santiago Alonso, Ángel González-Prieto
Neural Collaborative Filtering Classification Model to Obtain Prediction Reliabilities. Int. J. Interact. Multim. Artif. Intell. 7 (4) (2022)
Ángel González-Prieto, Abraham Gutiérrez, Fernando Ortega, Raúl Lara-Cabrera
ResBeMF: Improving Prediction Coverage of Classification based Collaborative Filtering. CoRR (2022)
Jessica Díaz, Daniel López-Fernández, Jorge Pérez, Ángel González-Prieto
Why are many businesses instilling a DevOps culture into their organization? Empir. Softw. Eng. 26 (2) (2021)
Daniel López-Fernández, Jessica Díaz, Javier García Martin, Jorge Pérez, Ángel González-Prieto
DevOps Team Structures: Characterization and Implications. CoRR (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)
Alberto Mozo, Ángel González-Prieto, Antonio Pastor Perales, Sandra Gómez Canaval, Edgar Talavera
Synthetic flow-based cryptomining attack generation through Generative Adversarial Networks. CoRR (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)
Jessica Díaz, Jorge Enrique Pérez-Martínez, Carolina Gallardo, Ángel González-Prieto
Applying Inter-rater Reliability and Agreement in Grounded Theory Studies in Software Engineering. CoRR (2021)
Fernando Ortega, Raúl Lara-Cabrera, Ángel González-Prieto, Jesús Bobadilla
Providing reliability in recommender systems through Bernoulli Matrix Factorization. Inf. Sci. 553 (2021)
Ángel González-Prieto, Alberto Mozo, Sandra Gómez Canaval, Edgar Talavera
Improving the quality of generative models through Smirnov transformation. CoRR (2021)
Jesús Bobadilla, Fernando Ortega, Abraham Gutiérrez, Ángel González-Prieto
Deep Variational Models for Collaborative Filtering-based Recommender Systems. CoRR (2021)
Ángel González-Prieto, Antonio Brú, Juan Carlos Nuño, José Luis González-Álvarez
Machine learning for risk assessment in gender-based crime. CoRR (2021)
Jessica Díaz, Daniel López-Fernández, Jorge Pérez, Ángel González-Prieto
Why are many business instilling a DevOps culture into their organization? CoRR (2020)
Fernando Ortega, Raúl Lara-Cabrera, Ángel González-Prieto, Jesús Bobadilla
Providing reliability in Recommender Systems through Bernoulli Matrix Factorization. CoRR (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)
Ángel González-Prieto, Jorge Pérez, Jessica Díaz, Daniel López-Fernández
Inter-Coder Agreement for Improving Reliability in Software Engineering Qualitative Research. CoRR (2020)
Jesús Bobadilla, Raúl Lara-Cabrera, Ángel González-Prieto, Fernando Ortega
DeepFair: Deep Learning for Improving Fairness in Recommender Systems. CoRR (2020)
Jesús Bobadilla, Ángel González-Prieto, Fernando Ortega, Raúl Lara-Cabrera
Deep Learning feature selection to unhide demographic recommender systems factors. CoRR (2020)