After nearly three years and entries from more than 50,000 contestants, a multinational team says that it has met the requirements to win the million-dollar Netflix Prize: It developed powerful algorithms that improve the movie recommendations made by Netflix’s existing software by more than 10 percent.Congrats to the winners. I hope other companies will adopt this contest method of innovation as well.
On Friday, a coalition of four teams calling itself BellKor’s Pragmatic Chaos — made up of statisticians, machine learning experts and computer engineers from America, Austria, Canada and Israel — declared that it has produced a program that improves the accuracy of the predictions by 10.05 percent.
Under the rules of the contest, Netflix said that other contestants now have 30 days to try to do even better. If they cannot, BellKor’s Pragmatic Chaos will collect the $1 million.
BellKor’s Pragmatic Chaos is a pretty elite crowd. The group is a collection of the 2007 and 2008 winners of the Netflix Progress Prizes — $50,000 a year for the teams that made the most progress toward the 10 percent improvement — and a pair of engineers from Montreal who have long been near the top of the contest’s leaderboard.
The team includes Bob Bell and Chris Volinsky of the statistics research department at AT&T Research (members of the 2007 and 2008 Progress Prize-winning teams); Andreas Toscher and Michael Jahrer, machine learning experts at Commendo research and consulting in Austria (members of the 2008 winning team); Martin Piotte and Martin Chabbert, engineers and founders of Pragmatic Theory in Montreal; and Yehuda Koren, a senior scientist at Yahoo Research in Israel (a member of the 2007 and 2008 winning teams).