International coalition qualifies for Netflix Prize

A coalition of four teams called BellKor's Pragmatic Chaos has qualified for the million-dollar Netflix Prize by creating a predictive model that generates movie recommendations with 10% greater accuracy than Netflix's current system. The New York Times has more, but at this point the details are still sketchy as competitors have 30 days to beat BellKor's performance:

Mr. Piotte, a founder of Pragmatic Theory, explained why he recently joined the larger team. “Because of the nature of the competition, making a coalition of teams is a quick way to improve results,” he said in an e-mail Friday night. “We felt that we had little chance to keep the lead against such a coalition unless we were part of one, too.”

But he declined to say just how the team nudged their work over the 10 percent threshold. “Since the competition remains open for 30 days, we are reluctant to disclose any secret at this time,” Mr. Piotte said. “All I can say is that we all worked very hard to achieve this mark, and that the final solution contains many original ideas.”

However in email today Chis Volinsky, of the AT&T Labs team in the coalition, gave me a few details. He said that R was used sparingly for some visualization and a little bit of model development, and that most of the heavy lifting was done in C++ with a little bit of SAS. It seems the teams worked quite independently: Chris isn't sure what the other collaborators used.

 

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