iTunes automatic music classifier & scribbler [Archived]

February 26, 2008


Title: iTunes automatic music classifier & scribbler
Duration: One Semester
Responsible TA: Nicolas Jones
Goals: Classify music (and, possibly, recommend better music or generate automatic playlists)
Keywords: iTunes, preference elicitation

iTunes already incorporates a rating mechanisms, a genre classification, a playlists categorisation, and a play-count log. Unfortunately, this information is very rarely used by iTunes to represent data in a semi-automatic way. Furthermore, a majority of users don’t use these at all, and the small subset of those who do spend a lot of time with it. We propose to write a plugin who will rely on the users’ implicit preferences (behaviour) to rate the songs, classify them by similarity in automated playlists, and possibly creating an improved online musical profile on sites like

Project Results:
  • automatic rating mechanisms
  • automatic playlists
  • implementation of audioscrobbler protocol for submitting to online profile (
Required Skills
  • Good programming skills
  • Previous experience with iTunes plugins is a plus