Music Discovery

Music discovery research aims to improve how users find new music they enjoy, addressing challenges like popularity bias and the need for diverse recommendations. Current efforts focus on developing sophisticated recommendation systems using graph neural networks and transformer models, leveraging user listening history, social connections, and even brainwave data to personalize recommendations and generate playlists. These advancements are impacting music streaming services by enhancing user experience and providing valuable insights into the complex interplay between music, social interaction, and individual preferences.