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It is our great honor to announce the $1M Grand Prize winner of the Netflix Prize contest as team BellKor's Pragmatic Chaos for their verified submission on July 26, 2009 at 18:18:28 UTC, achieving the winning RMSE of 0.8567 on the test subset. This represents a 10.06% improvement over Cinematch's score on the test subset at the start of the contest. We congratulate the team of Bob Bell, Martin Chabbert, Michael Jahrer, Yehuda Koren, Martin Piotte, Andreas Töscher and Chris Volinsky for their superb work advancing and integrating many significant techniques to achieve this result.The Prize was awarded in a ceremony in New York City on September 21st, 2009. We will post a video on this forum of the presentation the team delivered about their Prize algorithm. In accord with the Rules the winning team has prepared a system description consisting of three papers, which we both make public below. Team BellKor's Pragmatic Chaos edged out team The Ensemble with the winning submission coming just 24 minutes before the conclusion of the nearly three-year-long contest. Historically the Leaderboard has only reported team scores on the quiz subset. The Prize is awarded based on teams' test subset score. Now that the contest is closed we will be updating the Leaderboard to report team scores on both the test and quiz subsets. To everyone who participated in the Netflix Prize: You've made this a truly remarkable contest and you've brought great innovation to the field. We applaud you for your contributions and we hope you've enjoyed the journey. The Netflix Prize contest is now closed. We will soon be launching a new contest, Netflix Prize 2. Stay tuned for more details. The winning team's papers submitted to the judges can be found below. These papers build on, and require familiarity with, work published in the 2008 Progress Prize.Y. Koren, "The BellKor Solution to the Netflix Grand Prize", (2009).A. Töscher, M. Jahrer, R. Bell, "The BigChaos Solution to the Netflix Grand Prize", (2009).M. Piotte, M. Chabbert, "The Pragmatic Theory solution to the Netflix Grand Prize", (2009).
In 2009, the Netflix $1 Million Challenge brought a winning team with a game changing algorithm, but why did Netflix decide to thrash it?
We relate the Netflix Prize to the broader recommendation challenge, outline the external components of our personalized service, and highlight how our task evolved with the business.
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