EEMR: An Emotion-Enhancing Hybrid Recommendation Mechanism for Music Playlists

抄録

Affective states play a crucial role in music, as music can influence both current emotions and long-term moods. We propose a novel emotion-enhancing hybrid music recommendation (EEMR) mechanism that finds the suitable criteria in selecting the best music playlist for improving user’s emotion by combining two recommendation techniques, i.e., content-based filtering and context-aware approach. This mechanism generates playlists that align with the user’s preferences and current emotion, while also supporting gradual improvement of the user’s emotion over time.