Music cold-start and long-tail recommendation

Recent advances in deep learning have yielded new approaches for music recommendation in the long tail. The new approaches are based on data related to the music content (i.e. the audio signal) and context (i.e. other textual information), from which it automatically obtains a representation in a latent space that is used to generate the recommendations. The authors of these new approaches have shown improved accuracies, thus becoming the new state-of-the-art for music recommendation in the long tail.