Different users with a different musical background may have different ideas about what makes two music tracks sound similar. Hence, a similarity-based structuring of a music collection should reflect personal views.
Learn a personalized distance measure from the way a user interacts with the collection.
- hexagonal Growing Self-Organizing Map (GSOM) for structuring the collection into groups of similar tracks
- user feedback by assigning tracks to different groups (drag & drop)
- automatic adaptation of the track distance measure based on the new group assignment through quadratic programming
- implementation: Java using the processing.org framework for visualization