Netflix unveils $1 million prize winners

Movie rental company Netflix confirmed the lucky winners of a $1 million prize, sought for more than three years in a contest to improve the site's movie recommendation and ratings engine.

The winning team, BellKor, a seven-member group of researchers, scientists, and engineers from around the world, won the prize by managing to improve Netflix's movie recommendation system by just over 10 percent.

In 2006, Netflix introduced a $1 million prize competition that required contestants to improve movie recommendations for subscribers who regularly rate movies they watched. Netflix says 51,051 contestants from 186 countries have tried to come up with a better recommendation system.

Two years into the contest, Netflix started doubting that anyone would come with a solution. But in the end, two teams actually managed to improve Netflix's predictions engine equally (10.06 percent). The runners-up, Ensemble, lost because they submitted their entry a few minutes later than the winning team, BellKor.

The BellKor team includes two AT&T research staff, Bob Bell and Chris Volinsky; Yahoo's Israel Lab Yehuda Koren; Austrian researchers Andreas Töscher and Michael Jahrer; and Quebec-based Martin Chabbert and Martin Piotte.

Netflix said that the changes to the recommendation engine are yet to be implemented, as the algorithms contributing to the overall 10 percent improvement are very complex. Netflix hopes the changes will help the company retain subscribers.

(Via PC World)

Comments

Jessica said…
so how did they improve it? like what was their suggestion? I dont think the article stated how they made a difference...unless i missed that.

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