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Most music recommendations are based on collaborative filtering algorithms.  Sites like last.fm, goombah, qloud and iLike use the 'wisdom of the crowds' to find related artists or songs.   Using these techniques yield pretty good recommendations, but they could be better.  For instance, in a collaborative filtering system, the opinion of a highly-engaged music listener, the 'super-fan' if you will, counts the same as the casual or indifferent listener.  A CF system can't tell the difference between a Pitchfork music critic, listening to the latest Deerhoof album over and over so they can write the review, and a jogger that listens to the latest Deerhoof album over and over because it is good music for running.  A music recommender should recognize that not all opinions are created equal, that some people really do know better than others.    

One attempt at focusing on taste makers is the site When Killed Like Roosters.  WKLR is a music recommendation site that, unlike a traditional social recommender, will give extra weight to the opinions of the highly-engaged music listener.  WKLR mines the taste data of music bloggers, those that care enough about music to write about it - and provides charts of the most highly rated music based upon these tastemaker ratings.   WKLR seems to have gone quiet over the last few months - so this is not an idea that is taking over the world by storm. Still, I think we will be seeing more CF systems that try to find the taste makers and the trend setters and give the opinions of these individuals more weight.