:: MUSIC RECOMMENDATION TUTORIAL -- ISMIR 2007 ::: "As the world of online music grows, music recommendation systems become an increasingly important way for music listeners to discover new music. Commercial recommenders such as Last.fm and Pandora have enjoyed commercial and critical success. But how well do these systems really work? How good are the recommendations? How far into the 'long tail' do these recommenders reach? In this tutorial we look at the current state-of-the-art in music recommendation. We examine current commercial and research systems, focusing on the advantages and the disadvantages of the various recommendation strategies. We look at some of the challenges in building music recommenders and we explore some of the ways that Music Information Retrieval (MIR) techniques can be used to improve future recommenders."
It would have been great to see the informal survey extended to track-level recommendations (beyond just the artist level), but it is still very interesting even at this higher level.
On a related note, I will be on an panel next week at the Recommender Systems Conference in Minneapolis. Specifically the panel is:
Friday Afternoon Panel: Where should we be investing most in research and practice to increase value of recommenders?
* Moderator: Todd Beaupre, Yahoo, Inc.
* Joaquin Delgado, CTO, Lending Club Corp.
* Jason Herskowitz, VP of Consumer Products, MyStrands
* Kartik Hosanagar, Assistant Professor, Wharton School of Business, University of Pennsylvania
* David Jennings, DJ Alchemi LLC
* Zac Johnson, Product Manager, All Media Guide, Inc.