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From the Netflix prize FAQ:

Why not provide other data about the movies, like genres, directors, or actors?

We know others do. Again, Cinematch doesn’t currently use any of this data. Use it if you want.

That seems like an easy target - if I've 5-starred every movie with Kevin Spacey, I probably will like anything with Kevin Spacey. Why not mine blogs and reviews, trying to find themes which are appealing to individuals?

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It's probably just not that hot of a solution, believe it or not. The recommendation engine should be able to make much better associations between movies, without even being able to describe what those associations are. Looking at features like genre, director, actor etc, is like a spam filter looking for specific spammy words. As soon as the spammers start saying "p3n1s" instead or Eddy Murphy starts making family movies, it falls apart. Check out http://karmatics.com/docs/evolution-and-wisdom-of-crowds.htm... (scroll down to "3. Recommendation Systems" for the relevant part) for an explanation.

Great link. Thanks for posting that.

I think the limiting factor is the amount of computation required. When you take the number of variables (actors, directors, themes, box office gross, etc) x the number of values each of them have (dozens to thousands) x the number of users, that's a lot of crunching to do. Perhaps do some pre-crunching to find actors that have a correlation like that and then just check those. Apply the "Kevin Spacey index", if you will.

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