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Manuel Moussallam

Explainability in Music Recommender Systems

Jan 25, 2022
Darius Afchar, Alessandro B. Melchiorre, Markus Schedl, Romain Hennequin, Elena V. Epure, Manuel Moussallam

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* To appear in AI Magazine, Special Topic on Recommender Systems 2022

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Follow the guides: disentangling human and algorithmic curation in online music consumption

Sep 08, 2021
Quentin Villermet, Jérémie Poiroux, Manuel Moussallam, Thomas Louail, Camille Roth

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* (c) The Authors 2021. To be published in Proc. 15th ACM Conference on Recommender Systems (RecSys '21), Sep 27-Oct 1, 2021, Amsterdam, NL. 16 pages, 6 figures, 3 tables. This is the authors' version of the work. It is posted here for your personal use. Not for redistribution

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Hierarchical Latent Relation Modeling for Collaborative Metric Learning

Jul 26, 2021
Viet-Anh Tran, Guillaume Salha-Galvan, Romain Hennequin, Manuel Moussallam

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* 15th ACM Conference on Recommender Systems (RecSys 2021)

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Modeling the Music Genre Perception across Language-Bound Cultures

Oct 13, 2020
Elena V. Epure, Guillaume Salha, Manuel Moussallam, Romain Hennequin

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* 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020)

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Improving Collaborative Metric Learning with Efficient Negative Sampling

Sep 24, 2019
Viet-Anh Tran, Romain Hennequin, Jimena Royo-Letelier, Manuel Moussallam

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* SIGIR 2019

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Disambiguating Music Artists at Scale with Audio Metric Learning

Oct 03, 2018
Jimena Royo-Letelier, Romain Hennequin, Viet-Anh Tran, Manuel Moussallam

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* published in ISMIR 2018

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Music Mood Detection Based On Audio And Lyrics With Deep Neural Net

Sep 19, 2018
Rémi Delbouys, Romain Hennequin, Francesco Piccoli, Jimena Royo-Letelier, Manuel Moussallam

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* Published in ISMIR 2018

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