Isn't sparse recommendation for videos kind of solved in netflix prize, where the winner uses SVD to extract signature characteristic and recommend videos base on that?
The issue is that the Netflix dataset has a baked-in assumption that a recommender system should show media that a user is likely to have ranked highly. It may be more important to show the user media they wouldn't have found (and thus ranked) at all. Or perhaps a user will be more engaged with something controversial rather than generically acceptable. Who knows?
I think I'd rather have a random collection of titles than a recommended list for me.