9998

Bobadilla, J., Gutiérrez, A., Alonso, S., & González-Prieto, Á. (9998). Neural Collaborative Filtering Classification Model to Obtain Prediction Reliabilities. International Journal Of Interactive Multimedia And Artificial Intelligence, In Press(In Press), 1-9. http://doi.org/10.9781/ijimai.2021.08.010

2021

Bobadilla, J., Lara-Cabrera, R., González-Prieto, Á., & Ortega, F. (2021). DeepFair: Deep Learning for Improving Fairness in Recommender Systems. International Journal Of Interactive Multimedia And Artificial Intelligence, 6(Regular Issue), 86-94. http://doi.org/10.9781/ijimai.2020.11.001

Houari, N. S., & Taghezout, N. (2021). An Effective Tool for the Experts' Recommendation Based on PROMETHEE II and Negotiation: Application to the Industrial Maintenance. International Journal Of Interactive Multimedia And Artificial Intelligence, 6(Regular Issue), 67-77. http://doi.org/10.9781/ijimai.2021.01.002

2020

Bobadilla, J., Ortega, F., Gutiérrez, A., & Alonso, S. (2020). Classification-based Deep Neural Network Architecture for Collaborative Filtering Recommender Systems. International Journal Of Interactive Multimedia And Artificial Intelligence, 6(Special Issue on Soft Computing), 68-77. http://doi.org/10.9781/ijimai.2020.02.006

Bobadilla, J., Gutiérrez, A., Alonso, S., & Hurtado, R. (2020). A Collaborative Filtering Probabilistic Approach for Recommendation to Large Homogeneous and Automatically Detected Groups. International Journal Of Interactive Multimedia And Artificial Intelligence, 6(Regular Issue), 11. http://doi.org/10.9781/ijimai.2020.03.002

2018

Taghezout, N., Benkaddour, F. Z., Kaddour-Ahmed, F. Z., & Hammadi, I. -A. (2018). An Adapted Approach for User Profiling in a Recommendation System: Application to Industrial Diagnosis. International Journal Of Interactive Multimedia And Artificial Intelligence, 5(Regular Issue), 118-130. http://doi.org/10.9781/ijimai.2018.06.003

2015

Cordobés, H., Fernández Anta, A., Chiroque, L., Pérez, F., Santos, A., Leiva, R. G., et al. (2015). Empirical Comparison of Graph-based Recommendation Engines for an Apps Ecosystem. International Journal Of Interactive Multimedia And Artificial Intelligence, 3(Special Issue on Digital Economy), 33-39. http://doi.org/10.9781/ijimai.2015.324

2014

Burgos, D., & Corbi Bellot, A. (2014). Review of Current Student-Monitoring Techniques used in eLearning-Focused recommender Systems and Learning analytics. The Experience API & LIME model Case Study. International Journal Of Interactive Multimedia And Artificial Intelligence, 2(Special Issue on Multisensor User Tracking and Analytics to Improve Education and other Application Fields), 44-52. http://doi.org/10.9781/ijimai.2014.276

2013

Rodríguez, P., Tabares, V., Duque, N., Ovalle, D., & Vicari, R. (2013). BROA: An agent-based model to recommend relevant Learning Objects from Repository Federations adapted to learner profile. International Journal Of Interactive Multimedia And Artificial Intelligence, 2(Special Issue on Artificial Intelligence and Social Application), 6-11. http://doi.org/10.9781/ijimai.2013.211

Boff, E., & Reategui, B. (2013). Mining Social and Affective Data for Recommendation of Student Tutors. International Journal Of Interactive Multimedia And Artificial Intelligence, 2(Special Issue on Artificial Intelligence and Social Application), 32-38. http://doi.org/10.9781/ijimai.2013.214