When the organizers of the Netflix Prize contest announced late last week that one team had met the requirement for the $1 million Grand Prize, Yehuda Koren, a member of the seven-person multinational team, was in Paris to present a paper at KDD-09, the 15th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. The ideas he laid out won the conference's Best Paper Award — and, not coincidentally, had much to do with reaching the contest's target of improving the accuracy of Netflix movie recommendations by 10 percent. In the paper, Koren, a senior research scientist at Yahoo Research Israel in Haifa, showed a way to improve Netflix's recommender algorithm by using information about changes in the ratings over time. His role on the winning team, BellKor's Pragmatic Chaos , involved refining the model that deals with temporal dynamics.

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http://cacm.acm.org/news/32450-award-winning-paper-reveals-key-to-netflix-prize/fulltext