評論
打印
Netflix is offering $1 million to any group that can improve its user recommendations accuracy 10 percent, according to the May issue of IEEE Spectrum.
據電氣和電子工程師協會（IEEE）5月份的《波譜》雜志的報道，Netflix公司向任何能提高其電影用戶推薦準確度10個百分點的研究小組提供1百萬美元的獎勵。
Netflix isn’t satisfied with the way its system recommends new movies to customers based on their viewing habits. So the mail-order DVD rental company has offered outside teams prizes to improve its accuracy. A group from AT&T Laboratories has already won $50,000 for figuring out a formula that’s 8.43 percent better at telling a film buff what to rent. And Netflix is sweetening the pot—the team that can improve recommendation accuracy by 10 percent will get a cool million.
The contest requires that recommendations be made using the ratings customers give other movies they’ve rented. But the researchers say whether or not a person explicitly rates their returns, their rental history can be used as an “inferred rating” of things like genres or actors. What’s more, the preferences of other customers can predict how someone with similar rental histories would score a film. The research is explained in the May issue of the journal IEEE Spectrum.
There are certainly bigger problems to solve these days than recommending movies. But it would be nice to know why Netflix keeps insisting after I’ve returned Slumdog Millionaire and Delicatessen that I’d really like Annie.
Netflix根據顧客看電影的習慣來推薦新的電影，而他們對自己的這套系統并不滿意。這個辦理郵寄電影DVD業務的租賃公司向外界提供獎勵以期提高電影推薦的準確度。來自美國電話電報公司實驗室的（AT&T）一個研究小組計算出了一個公式，這個公式在告訴影迷們租那部電影方面，準確度提高了8.3%，他們因此獲得了5萬美元的獎勵。接著Netflix增加了獎勵金額——如果有研究小組能提高推薦準確度10個百分點的話，他們會得到整整1百萬美元。
競爭要求這些推薦是根據顧客對他們所租的其他電影的評級來確立的。但是，研究者們說，不管一個人是否明確地對他們還回來的影片進行評級，他們的租借歷史可以用作諸如電影類別或者演員們的“間接評級”。而且，其它顧客的偏愛能預測到和他具有類似租借歷史的的顧客如何評價一部電影。這項研究發表在5月份的電氣和電子工程師協會（IEEE）《波譜》雜志上。
除了推薦電影之外，當然目前還有一些更重要的問題有待解決。不過，如果能知道為什么在我看完了《貧民窟的百萬富翁》以及《黑店狂想曲》后，Netflix仍然堅持推薦我看《安妮》的話，這應該會是個不錯的主意。
