Kevin's Weblog

music similarity, e.g. for playlist generation. Problems -- lots of nodes, sparse similarity matrix, user collection doesn't necessarily match editorial recommendations. Interesting and seems to produce reasonable results. Similar discussion afterwards to the talk at overture recently: what makes a good playlist, how much similarity is actually desired?

Heirarchical Topic Models -- learning heirarchies of topics from a corpus, with possibility of growing the tree as new data is gathered. I want to understand this talk better. With only 20 minutes, it all went by too fast.

This conference is definitely a bit of a firehose. 20 minutes doesn't seem adequate for a lot of these talks unless you are already very familiar with the topic. However, this is a highly interdisciplinary conference so most people aren't, for any given talk. Plus, in addition to the 26 talks, there's something like 150 posters. I can't even slog through all the abstracts for the posters to figure out which ones I ought to visit.