Personalised Music Recommendation System

Personalised Music Recommendation System

Author Name : Yash Marke, Jatin Chainani, Yuvraj Singh, Sukanya Roychowdhury

ABSTRACT

As an important marketing tool, recommendation systems for information sites offer an opportunity for merchants to discover potential consumption tendencies and also increase the user engagement on information sites. This project puts forward a novel recommendation algorithm to make the recommendation system more accurate, personalized and intelligent. As online music streaming becomes the dominant medium for people to listen to their favorite songs, music streaming services are now able to collect large amounts of data on the listening habits of their customers. These streaming services, like Spotify, Apple Music or Pandora, are using this data to provide recommendations to their listeners. These music recommendation systems are part of a broader class of recommendation systems, which filter information to predict a user’s preferences when it comes to a certain item. 

Keywords: Sentiment analysis , Natural language processing , Facebook Graph API , Machine Learning