Culture-Aware Music Recommendation

Integrating information about the listener’s cultural background when building music recommender systems has recently been identified as a means to improve recommendation quality. In this paper, we therefore propose a novel approach to jointly model users by the user’s musical preferences and his/her cultural background. We describe the musical preferences of users by relying on the acoustic features of the songs the users have been listening to and characterize the cultural background of users by cultural and socio-economic features that we infer from the user’s country. To evaluate the impact of the proposed user model on recommendation quality, we integrate the model into a culture-aware music recommender system. We show that incorporating both acoustic information of the tracks a user has listened to as well as the cultural background of users in the form of a music-cultural user model contributes to improved recommendation performance.