Music Recommendation System using Content and Collaborative Filtering Methods

Abstract

Rapid development of mobile devices and internet has made possible for us to access different music resources freely. While the Music industry may favor certain forms of music over others, it's important to grasp that there isn’t one human culture on earth that has existed without music. during this paper, we've designed, implemented and analyzed a song recommendation system. we've used Song Dataset provided to search out correlations between users and songs and to find out from the previous listening history of users to supply recommendations for songs which users would like to concentrate most. The dataset contains over ten thousand songs and listeners are recommended the simplest available songs supported the mood, genre, artist and top charts of that year. With an interactive UI we show the listener the highest songs that were played the foremost and top charts of the year. Listener even have the choice to pick out his/her favorite artist and genres on which songs are recommended to them using the dataset. Keywords- Collaborative model, Content based model, Recommendation System, Popularity model