[HTML][HTML] Deep learning in music recommendation systems
M Schedl - Frontiers in Applied Mathematics and Statistics, 2019 - frontiersin.org
Like in many other research areas, deep learning (DL) is increasingly adopted in music
recommender systems (MRS). Deep neural networks are used in this area particularly for …
recommender systems (MRS). Deep neural networks are used in this area particularly for …
Music deep learning: deep learning methods for music signal processing—a review of the state-of-the-art
The discipline of Deep Learning has been recognized for its strong computational tools,
which have been extensively used in data and signal processing, with innumerable …
which have been extensively used in data and signal processing, with innumerable …
Feature-combination hybrid recommender systems for automated music playlist continuation
Music recommender systems have become a key technology to support the interaction of
users with the increasingly larger music catalogs of on-line music streaming services, on …
users with the increasingly larger music catalogs of on-line music streaming services, on …
Attributes Relevance in Content-Based Music Recommendation System
D Kostrzewa, J Chrobak, R Brzeski - Applied Sciences, 2024 - mdpi.com
The possibility of recommendations of musical songs is becoming increasingly required
because of the millions of users and songs included in online databases. Therefore …
because of the millions of users and songs included in online databases. Therefore …
Surveying More Than Two Decades of Music Information Retrieval Research on Playlists
In this article, we present an extensive survey of music information retrieval (MIR) research
into music playlists. Our survey spans more than 20 years, and includes around 300 papers …
into music playlists. Our survey spans more than 20 years, and includes around 300 papers …
Order, context and popularity bias in next-song recommendations
The availability of increasingly larger multimedia collections has fostered extensive research
in recommender systems. Instead of capturing general user preferences, the task of next …
in recommender systems. Instead of capturing general user preferences, the task of next …
Automatic playlist generation using convolutional neural networks and recurrent neural networks
Nowadays, a great part of music consumption on music streaming services are based on
playlists. Playlists are still mainly manually generated by expert curators, or users, process …
playlists. Playlists are still mainly manually generated by expert curators, or users, process …
Controllable music playlist generation based on knowledge graph and reinforcement learning
In this study, we propose a novel music playlist generation method based on a knowledge
graph and reinforcement learning. The development of music streaming platforms has …
graph and reinforcement learning. The development of music streaming platforms has …
Machine learning approaches to hybrid music recommender systems
Music recommender systems have become a key technology supporting the access to
increasingly larger music catalogs in on-line music streaming services, on-line music shops …
increasingly larger music catalogs in on-line music streaming services, on-line music shops …
Global-Local Similarity Function for Automatic Playlist Generation
H Cheng, R Zhang, X Huang… - 2022 IEEE International …, 2022 - ieeexplore.ieee.org
This paper proposes the Global-Local Similarity Function (GLSF) to exploit the multi-scale
cues in track sequences for automatic playlist generation (APG). Unlike previous …
cues in track sequences for automatic playlist generation (APG). Unlike previous …