LUIS
MARTÍNEZ LÓPEZ
CATEDRATICO DE UNIVERSIDAD
Jorge
Castro
Publicaciones en las que colabora con Jorge Castro (14)
2020
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Natural Noise Management in Recommender Systems Using Fuzzy Tools
Studies in Computational Intelligence (Springer Verlag), pp. 1-24
2019
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A Big Data Semantic Driven Context Aware Recommendation Method for Question-Answer Items
IEEE Access, Vol. 7, pp. 182664-182678
2018
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A fuzzy approach for natural noise management in group recommender systems
Expert Systems with Applications, Vol. 94, pp. 237-249
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Group Recommendations Based on Hesitant Fuzzy Sets
International Journal of Intelligent Systems, Vol. 33, Núm. 10, pp. 2058-2077
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Opinion Dynamics-Based Group Recommender Systems
IEEE Transactions on Systems, Man, and Cybernetics: Systems, Vol. 48, Núm. 12, pp. 2394-2406
2017
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A recommender system for supporting students in programming online judges
Smart Innovation, Systems and Technologies
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An empirical study of natural noise management in group recommendation systems
Decision Support Systems, Vol. 94, pp. 1-11
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Dealing with diversity and novelty in group recommendations using Hesitant fuzzy sets
IEEE International Conference on Fuzzy Systems
2016
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A fuzzy model for managing natural noise in recommender systems
Applied Soft Computing Journal, Vol. 40, pp. 187-198
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An approach for natural noise management in recommender systems using fuzzy logic
Uncertainty Modelling in Knowledge Engineering and Decision Making - Proceedings of the 12th International FLINS Conference, FLINS 2016
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Managing natural noise in recommender systems
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
2015
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A consensus-driven group recommender system
International Journal of Intelligent Systems
2014
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Improving group recommendation with outlier data filtering
Decision Making and Soft Computing - Proceedings of the 11th International FLINS Conference, FLINS 2014
2012
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A context-aware mobile recommender system based on location and trajectory
Advances in Intelligent Systems and Computing