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 talk we look at the current state-of-the-art in music recommendation and music discovery in the Web.
But...which Web? the old-fashioned one that we all are used to? The "Web 2.0"? The "Semantic Web"?
And, how does these "environments" affect music recommendation strategies and social media interaction? This talk will present real examples that emphasize the uppers and downers of the different coexisting webs.
Furthermore, we will present the current tools that the Music Information Retrieval field offers to improve/refine the resulting recommendations, as well as easing the life to Content Providers when annotating huge music collections.