“The new challenge focuses on predicting the movie preferences of people who rarely or never rate the movies they rent. This will be deduced from more than 100 million data points, including information about renters’ ages, genders, ZIP codes, genre ratings and previously chosen movies.
Instead of a single $1 million prize, this new challenge will be split into one $500,000 award to the team judged to be leading after six months and an additional $500,000 to the team in the lead at the 18-month mark, when the contest is wrapped up.”
The team’s 10 percent achievement will not be immediately incorporated into Netflix.com, said Neil Hunt, chief product officer.
“There are several hundred algorithms that contribute to he overall 10 percent improvement – all blended together,” Hunt said. “In order to make the computation feasible to generate the kinds of volumes of predictions that we needed for a real system – we’ve selected just a small number – two or three of those algorithms for direct implementation.”