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Netflix Prize May Have Been Achieved
MadAnalyst writes "The long-running $1,000,000 competition to improve on the Netflix Cinematch recommendation system by 10% (in terms of the RMSE) may have finally been won. Recent results show a 10.05% improvement from the team called BellKor's Pragmatic Chaos, a merger between some of the teams who were getting close to the contest's goal. We've discussed this competition in the past."
Background: The Netflix Prize is an ongoing open competition for the best collaborative filtering algorithm that predicts user ratings for films, based on previous ratings. The competition is held by Netflix, an online DVD-rental service, and is opened for anyone (with some exceptions). The grand prize of $1,000,000 is reserved for the entry which bests Netflix's own algorithm for predicting ratings by 10%.
Well, just like the Ansari X Prize didn't cover the costs of developing and launching a suborbital rocket, the Netflix Prize isn't really meant to be a large enough prize to fully fund the development of a new recommendation algorithm. The purpose of the prize is to stimulate interest and get people started. The real reward will come when they turn their algorithm into commercialized software - the rewards from making such a thing applicable outside of Netflix could be large indeed.
We all know what to do, but we don't know how to get re-elected once we have done it
Pretty sure having it on their CV means they can effectively write their own pay cheque in terms of job opportunities.
+1 IDisagreeSoHeMustBeATrollOrAnAstroturferOrAShill
I published a paper using Netflix data. (Yeah, that group.)
It's certainly cool that they beat the 10% improvement, and it's a hell of a deal for Netflix, since it would have cost them more than a prize money paid out to hire the researchers, the interesting thing is whether or not this really advances the the field of recommendation systems.
The initial work definitely did, but I wonder how much of the quest for the 10% threshold moved the science, as opposed to just tweaking an application. Recommender systems still don't bring up rare items, and they still have problems with diversity. None of the Netflix Prize work address any of these problems.
Still, I look forward to their paper.
from the excellent nyt article about the competition in november:
http://science.slashdot.org/article.pl?sid=08/11/22/0526216
it isn't bad movies that are the problem, taste in bad movies can still be uniform
the real problem is extremely controversial movies, most notably Napoleon Dynamite
http://www.imdb.com/title/tt0374900/
not controversial in terms of dealing with abortion or gun control, but controversial in terms of some people really found the movie totally stupid, while some people really found the movie to be really funny
movies like napolean dynamite are genre edge conditions, and people who apparently agree on everything else about movies in general encounter movies like this one and suddenly dramatically differ on their opinion of it, in completely unpredictable ways
intellectual property law is philosophically incoherent. it is your moral duty to ignore it or sabotage it