Music Recommendation System using Content and Collaborative Filtering Methods

Music Recommendation System using Content and Collaborative Filtering Methods

Swapna Singh , Vaibhav Kumar Singh , Rishabh Negi ,Aariz pathan ,Ayush Malik

Department of Computer Science and Engineering INDRAPRASTHA ENGINEERING COLLEGE

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