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At CES this  week, Gracenote announced a new product called 'Discover' that will provide music recommendation services for online music services. Gracenote Discover is using 3 techniques:

• Music experts label the music with 'micro-genres' a fine grained set of genre labels (they claim to use 1600 genres).
• Content-based - using 'DSP technology'
• Community Preferences - collaborative filtering such as one finds at Amazon.com.

Gracenote says that their engine is the Industry's First Global Multi-Method Music Recommendation Engine that "ensures the optimal music is recommended every time". 

The claim 'ensures he optimal music is recommended every time" makes me smile a bit.  Anyone who has worked with any kind of recommender engine, and especially with music recommendation based upon acoustic similarity knows that there is no such thing as an optimal music recommender.  In fact, music information retrieval researchers are still trying to figure out how to compare similarity engines to determine if one is better than another.  The problem, of course,  is that music similarity is a very subjective metric.  I may think two songs are similar because of the lyric content, while someone else may think they are very different based upon the intstrumetation.  There's no right answer.  The same holds true for music recommendation in general. There's never a 'right answer', so saying that a system ensures the optimal music is recommended is, well, rather funny.

Here is the press release: Gracenote Introduces Discover -- Industry's First Global Multi-Method Music Recommendation Engine