Regularizing Knowledge Transfer in Recommendation With Tag-Inferred Correlation
Peng Hao, Guangquan Zhang, Luis Martínez, Jie LuRegularizing Knowledge Transfer in Recommendation With Tag-Inferred Correlation
IEEE Transactions on Cybernetics, vol. 49, n.º 1. pp. 83-96, 2019.
A food recommender system considering nutritional information and user preferences
Raciel Yera, A. A. Alzahrani, Luis MartínezA food recommender system considering nutritional information and user preferences
IEEE Access, vol. 7, n.º 1. pp. 96695-96711, 2019.
On-line-food-nutrition.pdf8.72 MB
A fuzzy approach for natural noise management in group recommender systems
Jorge Castro, Raciel Yera, Luis MartínezA fuzzy approach for natural noise management in group recommender systems
Expert Systems with Applications, vol. 94. pp. 237-249, 2018.
Opinion Dynamics-Based Group Recommender Systems
Jorge Castro, Jie Lu, Guangquan Zhang, Yucheng Dong, Luis MartínezOpinion Dynamics-Based Group Recommender Systems
IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 48, n.º 12. IEEE, pp. 2394-2406, 2018.
An empirical study of natural noise management in group recommendation systems
Jorge Castro, Raciel Yera, Luis MartínezAn empirical study of natural noise management in group recommendation systems
Decision Support Systems, vol. 94. pp. 1-11, 2017.
Fuzzy Tools in Recommender Systems: A Survey
Raciel Yera, Luis MartínezFuzzy Tools in Recommender Systems: A Survey
International Journal of Computational Intelligence Systems, vol. 10. pp. 776-803, 2017.
ijcis_10_776_803.pdf2.35 MB
Managing Natural Noise in Recommender Systems
Luis Martínez, Jorge Castro, Raciel YeraManaging Natural Noise in Recommender Systems
5th International Conference on Theory and Practice of Natural Computing (TPNC 2016). Sendai (Japan): Springer, pp. 3-17, 2016.
Métodos de preprocesamiento de datos para sistemas recomendadores de filtrado colaborativo, con aplicación en un escenario de e-learning
Raciel Yera, Yailé Caballero Mota, Luis MartínezMétodos de preprocesamiento de datos para sistemas recomendadores de filtrado colaborativo, con aplicación en un escenario de e-learning
Santa Clara: , 2015.
tesis Raciel final.pdf2.55 MB
Correcting noisy ratings in collaborative recommender systems
Raciel Yera, Y Caballero, Luis MartínezCorrecting noisy ratings in collaborative recommender systems
Knowledge-based Systems, vol. 76. Elsevier, pp. 96-108, 2015.
publicado.pdf623.61 KB
Weighting of Features in Content-Based Filtering with Entropy and Dependence Measures
Jorge Castro, Rosa María Rodríguez, Manuel José BarrancoWeighting of Features in Content-Based Filtering with Entropy and Dependence Measures
International Journal of Computational Intelligence Systems, vol. 7. Taylor and Francis, pp. 80-89, 2014.