Netflix Progress Prize for 2008 宣布了

Netflix Prize 官方網站在12月10日宣布,今年(2008)的年度成就獎頒給 BellKor in BigChaos.

It is our great honor to announce the winner of the Netflix Progress Prize for 2008 as team BellKor in BigChaos for their verified just-in-time submission on Sept 30 at 21:17:40 UTC achieving a 9.44% improvement over Cinematch. We congratulate the team of Yehuda Koren, Robert Bell and Chris Volinsky of AT&T Research Labs combined with Andreas Töscher and Michael Jahrer of Commendo Research for their superb work integrating many significant techniques to achieve this result.

In accord with the Rules the team has prepared a system description consisting of two papers, which we both make public below. We will be awarding the Prize in a presentation at the Netflix offices in Los Gatos on December 17, 2008 at 4pm. Andreas Töscher and Michael Jahrer will present a public talk at that time about their Prize algorithm. We will post a video of that presentation via the Forum.

BellKor 團隊在網站上提供該團隊所發表與本次競賽有關的論文,供有興趣的讀者下載參考:


  • The BellKor 2008 Solution to the Netflix Prize. This is the document which lays out our overall strategy - as was required in the rules of the competition in order to claim the Progress Prize.

  • Factorization Meets the Neighborhood: a Multifaceted Collaborative Filtering Model. KDD 2008..

  • Recent Progress in Collaborative Filtering. RecSys 2008

  • Factor in the Neighbors: Scalable and Accurate Collaborative Filtering. submitted

  • Chasing $1,000,000: How We Won The Netflix Progress Prize. ASA Statistical and Computing Graphics Newsletter. Volume 18, Number 2.

  • Lessons from the Netflix Prize Challenge. SIGKDD Explorations, Volume 9, Issue 2.

  • The BellKor Solution to the Netflix Prize. This is the document which lays out our overall strategy - as was required in the rules of the competition in order to claim the Progress Prize.

  • Scalable Collaborative Filtering with Jointly Derived Neighborhood Interpolation Weights. ICDM 2007.

  • Improved Neighborhood Based Collaborative Filtering. KDD 2007 Netflix Competition Workshop.

  • Modelling relationships at Multiple Scales to Improve Accuracy of Large Recommender Systems. KDD 2007 .

  • Comments

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