Netflix awards $1-million research prize – new contest announced

September 23, 2009

(ChattahBox) — Netflix has awarded $1 million to a team of researchers who figured out how to improve the movie recommendations its engine makes to subscribers by more than 10 percent. The new algorithm by BellKor’s Pragmatic Chaos, a team of seven engineers, mathematicians, and computer scientists evaluates the preferences of users who rate a lot of movies to improve the companies ability to predict what movies its’ average customer will like. BellKor reportedly beat out another team, the Ensemble, with more than 30 members—that had achieved the exact same ratings improvement (10%) but lost by turning in its method 20 minutes after BellKor.

Netflix has also announced a new contest, with a $1 million prize for improving recommendations to users who seldom, or never rate movies.  Unlike the first challenge, the contest will have no specific accuracy target. Instead, $500,000 will be awarded to the team in the lead after the first six months, and $500,000 to the leader after 18 months.  The new Netflix contest has many concerned for invasion of its customers’ privacy. The new contest according to the New York Times is going to present the contestants with demographic and behavioral data, and they will be asked to model individuals’ “taste profiles,” the company said. The data set of more than 100 million entries though supposedly anonymous, will include information about renters’ ages, gender, ZIP codes, genre ratings and previously chosen movies.”  Perhaps companies with ulterior motives disguised as contestants could be handed this data for free with the intent to exploit?


Comments

Got something to say? **Please Note** - Comments may be edited for clarity or obscenity, and all comments are published at the discretion of ChattahBox.com - Comments are the opinions of the individuals leaving them, and not of ChattahBox.com or its partners. - Please do not spam or submit comments that use copyright materials, hearsay or are based on reports where the supposed fact or quote is not a matter of public knowledge are also not permitted.