Islands of Music

It all started about 7 years ago when I was an intern working in Aberdeen (Scotland). Aberdeen is a rather quiet town. It's beach was a wonderful place to sit and think about my MSc thesis which I was working on at that time.

At first I was very enthusiastic about the idea of using a metaphor of islands to visualize a music collection. However, a few years and many not so perfect island of music maps later my enthusiasm had faded away and I had more or less given up trying to map the entire music world onto a map.

Recently at Last.fm we launched our playground and one response we heard a few times was that it wasn't very colorful. (All three initial demonstrations were basically simple lists of artists or tracks.) At the same time I had a dataset of users described in terms of tags loaded in Matlab. Previous results using simple clustering algorithms had shown that it was very easy to extract meaningful clusters.

Now there's an islands of music demonstration on playground. There's also a journal entry talking about how it was computed.

Justin Donaldson’s Blog

For some reason I only found Justin’s blog today. The first time I heard of Justin was when I stumbled upon the visualizations he implemented at MyStrands. Basically he visualizes songs as little disks which are spread out on the screen according to similarity. He uses a modified version of (2-dimensional) MDS and he implemented a clever way to deal with songs that overlap spatially in the visualization. It's quite different from, for example, the way Paul uses (3-dimensional) MDS to visualize a music space.

Justin’s blog covers different topics, not all of which are related to MIR, but some of his entries are. For example, in this entry he addressed reviewer feedback regarding a paper he submitted on his MyStrands visualization. The blog entry's character is kind of similar to mine on the reviewer feedback I received for the MusicSun paper. Personally, I found it interesting to see that he was confronted with similar feedback as I have in the past: “Why is the visualization more informative/useful to a user than a ranked list of results?” In times where the simple Google style search interface dominates despite having so many nice visual alternatives (like kartOO) there is actually a need to explain this although it seems so obvious sometimes.

It seems to me that publishing a paper on a visual interface for music recommendation is much harder than publishing one about a genre classifier that achieves 100% classification accuracy (which isn't hard if the test set contains the same artists as the training set). I like how Justin implemented his visualization as part of a real music site (instead of just building a research prototype). I wonder if Justin couldn’t have easily conducted a simple evaluation using all the data gathered from that test. (Maybe just simple usage statistics over time?) I wonder if those statistics would be similar to the Alexa statistics for kartOO over the last years. Maybe visualizations that need more than one color and more than one dimension are too complex for music recommendation systems?

Btw, seems like Justin will be giving an interesting talk at the Recommendation Systems 2007 conference (as part of the doctoral symposium) and he’s also presenting a poster at ISMIR 2007.