Music Information Retrieval continues to be an excellent place to play around with the intersection of search, recommendation, user-guided exploration, and explanatory (transparent) algorithms.
First, check out the announcement of Music Explaura from Stephen Green at Sun Research. Stephen writes:
On the left of the artist page, you see the list of similar artists generated by the AURA recommenders. This list of artists is generated using a technique that’s quite a bit different than you’re probably used to. Rather than relying on the wisdom of the crowds via a technique like collaborative filtering, the AURA system computes the similarity between artists by computing the similarity between their textual auras.
Second, See Paul Lamere’s writeup, “Music Discovery is a Conversation, Not a Dictatorship“. Paul writes:
The Music Explaura gives us a hint of what music discovery will be like in the future. Instead of a world where a music vendor gives you a static list of recommended artists we’ll live in a world where the recommender can tell you why it is recommending an item, and you can respond by steering the recommendations away from things you don’t like and toward the things that you do like. Music discovery will no longer be a dictatorship, it will be a two-way conversation.
This is really cool stuff, and I hope the ideas behind steerable recommendations will start to work their way out into all types of search and recommendation, from Amazon-style purchase recommendations to standard web search itself.