Content-based Music Recommendation System

Building a music recommendation system is one of information retrieval tasks. This research is devoted to a content-based music recommender system. The main peculiarity of our work is that the developed recommender system is based on the acoustic similarity of musical compositions. Two approaches of building a content-based music recommender system are considered in this paper. The first is a quite common approach that uses acoustic features analysis. The second approach includes deep learning and computer vision methods application aimed at improving the results of the recommender system.