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The Netflix Prize was an open competition for the best collaborative filtering algorithm to predict user ratings for films, based on previous ratings without any other information about the users or films, i.e. without the users being identified except by numbers assigned for the contest.
With the elimination of the five-star rating system, we're looking back at the Netflix Prize competition that changed the company forever.
Refresh. Dataset from Netflix's competition to improve their reccommendation algorithm.
Like BellKor's Pragmatic Chaos, the winner of the Netflix Prize, second-place The Ensemble was an amalgam of teams which had been competing individually for the million-dollar prize.
In October 2006, Netflix launched the Netflix Prize, a competition aimed at improving its recommendation algorithm by at least 10%. The challenge was formidable: participants were provided with...
São Paulo, November 1, 2023 — Wednesday, on the closing night of the São Paulo International Film Festival, Netflix announced the film Bittersweet Rain as the winner of the first edition of the Netflix Prize.
The Netflix Prize and the Recommendation Problem. In 2006 we announced the Netflix Prize, a machine learning and data mining competition for movie rating prediction. We offered $1 million to whoever improved the accuracy of our existing system called Cinematch by 10%.
Million Dollar Netflix Prize Won. At last, it's official: the research team known as BellKor has won the $1 million Netflix Prize by improving the accuracy of the Netflix recommender algorithm by ...
A team of researchers Monday won a $1 million prize for developing a formula that improves the accuracy of the Netflix movie recommendation algorithm " beating another team by just 20 minutes.
In 2006, Netflix announced a competition to improve their existing recommendation system. They released a data set containing millions of ratings that contestants could use to design their systems, and they promised a $1,000,000 prize to the first contestants to beat Netflix's system by %10 or more.