I get a fair number of people approaching me to tell me that their music recommender system is the best because of [insert special secret sauce here]. Usually this doesn't go much further: after all, the sauce is secret and can't be shared; so I say I'll be interested to keep in touch with their progress, and I bite my lip to resist repeating my sceptical view that any recommender system only has to be good enough to keep people coming back for more recommendations.
In the case of Berlin-based mufin.com, launching in private beta today, the story is slightly different, as they sent me all their publicity release information, and Petar Djekic was willing to talk to me on the record as it were. They even gave me an invite code to give away — that's my disclosure out of the way!
Mufin.com grew out of the Fraunhofer Institute, also the birthplace of the MP3 format, and the technically interesting part of what they're doing builds on that strong research base in audio and acoustics. What mufin.com does is known as content-based filtering rather than collaborative user-based filtering. In other words, rather than saying "people who like this artist/song also like this artist/song", it says "this song is similar in important ways to this song, so if you like one, you may like the other". Or in other words, think more like Pandora than Last.fm.