Diego Sánchez-Moreno
Orcid: 0000-0003-0682-6594
According to our database1,
Diego Sánchez-Moreno
authored at least 14 papers
between 2013 and 2021.
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Bibliography
2021
Dynamic inference of user context through social tag embedding for music recommendation.
CoRR, 2021
Proceedings of the Distributed Computing and Artificial Intelligence, 2021
2020
Exploiting the User Social Context to Address Neighborhood Bias in Collaborative Filtering Music Recommender Systems.
Inf., 2020
Time-Aware Music Recommender Systems: Modeling the Evolution of Implicit User Preferences and User Listening Habits in A Collaborative Filtering Approach.
CoRR, 2020
A Session-Based Song Recommendation Approach Involving User Characterization along the Play Power-Law Distribution.
Complex., 2020
Using Social Tag Embedding in a Collaborative Filtering Approach for Recommender Systems.
Proceedings of the IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, 2020
2018
Proceedings of the 2018 IEEE/WIC/ACM International Conference on Web Intelligence, 2018
Inferring User Expertise from Social Tagging in Music Recommender Systems for Streaming Services.
Proceedings of the Hybrid Artificial Intelligent Systems - 13th International Conference, 2018
Moodsically. Personal Music Management Tool with Automatic Classification of Emotions.
Proceedings of the Distributed Computing and Artificial Intelligence, 2018
Social Influence-Based Similarity Measures for User-User Collaborative Filtering Applied to Music Recommendation.
Proceedings of the Distributed Computing and Artificial Intelligence, 2018
Proceedings of the Distributed Computing and Artificial Intelligence, 2018
2017
Recommendation of Songs in Music Streaming Services: Dealing with Sparsity and Gray Sheep Problems.
Proceedings of the Trends in Cyber-Physical Multi-Agent Systems. The PAAMS Collection, 2017
2016
A collaborative filtering method for music recommendation using playing coefficients for artists and users.
Expert Syst. Appl., 2016
2013
TV-SeriesRec: A Recommender System Based on Fuzzy Associative Classification and Semantic Information.
Proceedings of the Trends in Practical Applications of Agents and Multiagent Systems, 2013