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Found 13 papers, 9 papers with code
Modéliser la perception des genres musicaux à travers différentes cultures à partir de ressources linguistiques (Modeling the Music Genre Perception across Language-Bound Cultures )
Nous résumons nos travaux de recherche, présentés à la conférence EMNLP 2020 et portant sur la modélisation de la perception des genres musicaux à travers différentes cultures, à partir de représentations sémantiques spécifiques à différentes langues.
Let's Get It Started: Fostering the Discoverability of New Releases on Deezer
This paper presents our recent initiatives to foster the discoverability of new releases on the music streaming service Deezer.
On the Consistency of Average Embeddings for Item Recommendation
A prevalent practice in recommender systems consists in averaging item embeddings to represent users or higher-level concepts in the same embedding space.
Track Mix Generation on Music Streaming Services using Transformers
This paper introduces Track Mix, a personalized playlist generation system released in 2022 on the music streaming service Deezer.
Attention Mixtures for Time-Aware Sequential Recommendation
Transformers emerged as powerful methods for sequential recommendation.
A Scalable Framework for Automatic Playlist Continuation on Music Streaming Services
Music streaming services often aim to recommend songs for users to extend the playlists they have created on these services.
New Frontiers in Graph Autoencoders: Joint Community Detection and Link Prediction
It is still unclear to what extent one can improve CD with GAE and VGAE, especially in the absence of node features.
Flow Moods: Recommending Music by Moods on Deezer
We detail the motivations, the development, and the deployment of this system on Deezer.
Contributions to Representation Learning with Graph Autoencoders and Applications to Music Recommendation
In the last part of this thesis, we evaluate our methods on several graphs extracted from the music streaming service Deezer.
Modularity-Aware Graph Autoencoders for Joint Community Detection and Link Prediction
Graph autoencoders (GAE) and variational graph autoencoders (VGAE) emerged as powerful methods for link prediction.
Cold Start Similar Artists Ranking with Gravity-Inspired Graph Autoencoders
In this paper, we model this cold start similar artists ranking problem as a link prediction task in a directed and attributed graph, connecting artists to their top-k most similar neighbors and incorporating side musical information.
Hierarchical Latent Relation Modeling for Collaborative Metric Learning
Existing extensions of CML also either ignore the heterogeneity of user-item relations, i. e. that a user can simultaneously like very different items, or the latent item-item relations, i. e. that a user's preference for an item depends, not only on its intrinsic characteristics, but also on items they previously interacted with.
A Semi-Personalized System for User Cold Start Recommendation on Music Streaming Apps
This is commonly referred to as the user cold start problem.
