Hybrid music recommendation system: Enhanced collaborative filtering using context and interest based approach

In this paper, we propose an enhancement to the collaborative filtering, by combining context and interest of the user to give recommendations. The primary approach is based on the user´s contextual information that is influenced by various seasonal, atmospheric, situation and location oriented conditions. The secondary approach is based on the user´s interest of particular songs along with the choice of songs of other users with similar interest. This combined approach enhances the relevancy constraint of recommended songs to the user´s mood and interest.