Rhapsody will enable users to visualize their music in new ways. We will generate and show a dynamic graph showing connections between a user’s favorite songs, artists, and genres, and use that to help them discover new music.
The website “music-map.com” (see next section provides a simple visual analog for what we hope to accomplish, but we also want to incorporate the music that a user actually listens to, and we want to include individual songs. We plan to enable this feature by integrating with the user’s Spotify account.
Music-map.com has done a very similar thing in terms of the visualization they provide. Rhapsody will build on this functionality by incorporating social features and advanced recommendation tools. If you are friends with someone on Rhapsody, their music data points will help inform recommendations for you as well as your own data points.
Our data will come from The Echo Nest database, which is owned by Spotify and available through a public API. See this and this. The Echo Nest contains over a billion data points about more than 38 million songs. Before we deploy the application, we will construct our own database containing information from the API; the application will not talk to the API during runtime, only to our own database.
The core feature of our project will be the advanced graph traversal function (see below).
We will have two kinds of users: admins and regular users. Admins will have the ability to insert, update, and delete songs from the database. Regular users will have the ability to submit a request to insert/update/delete songs in case they find some information that is incorrect, or they release a new song and want to add it to the database. This way, we can leverage the community of users to make sure the database is accurate, but also prevent the average user from messing everything up.
Any user will have the ability to search and view results in a graph (or list). They will be able to search based on song title, artist, genre, key, etc.
Another planned feature is the party playlist, a shared playlist based on the combined recommendations for a group of users.
This feature can suggest songs based on other songs, albums, artists, genres, playlists, or the songs in the user’s library. The feature will implement a distance function to rate the similarity of songs and use the nearest neighbors as the recommendations.
This feature is the core value proposition of our project. By allowing users to explore (traverse) their network of music preferences in a visual and dynamic way, we introduce an exciting and modern genre of music discovery.
- Andrew Munch
- Madeline Kusters
- Mark Pruitt
- Will Badart
Read the project proposal here.