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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.
据电气和电子工程师协会（IEEE）5月份的《波谱》杂志的报道，Netflix公司向任何能提高其电影用户推荐准确度10个百分点的研究小组提供1百万美元的奖励。
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根据顾客看电影的习惯来推荐新的电影，而他们对自己的这套系统并不满意。这个办理邮寄电影DVD业务的租赁公司向外界提供奖励以期提高电影推荐的准确度。来自美国电话电报公司实验室的（AT&T）一个研究小组计算出了一个公式，这个公式在告诉影迷们租那部电影方面，准确度提高了8.3%，他们因此获得了5万美元的奖励。接着Netflix增加了奖励金额——如果有研究小组能提高推荐准确度10个百分点的话，他们会得到整整1百万美元。
竞争要求这些推荐是根据顾客对他们所租的其他电影的评级来确立的。但是，研究者们说，不管一个人是否明确地对他们还回来的影片进行评级，他们的租借历史可以用作诸如电影类别或者演员们的“间接评级”。而且，其它顾客的偏爱能预测到和他具有类似租借历史的的顾客如何评价一部电影。这项研究发表在5月份的电气和电子工程师协会（IEEE）《波谱》杂志上。
除了推荐电影之外，当然目前还有一些更重要的问题有待解决。不过，如果能知道为什么在我看完了《贫民窟的百万富翁》以及《黑店狂想曲》后，Netflix仍然坚持推荐我看《安妮》的话，这应该会是个不错的主意。
