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eView: Why the Netflix Prize Is a Good Start to Personalized Recommendations

Netflix created the $1 million Netflix Prize in 2006 as a way to reward developers of a next-generation film-rating prediction algorithm.

The idea sounded seductively simple: If developers could predict how users would rate a film, they could use that prediction to decide whether it makes sense to recommend the film to them or not.

The winner would be the first person to develop an algorithm capable of predicting user ratings of films at least 10 percent more accurately than Netflix’s internally developed Cinematch algorithm. Three years and 43,000 entries later — from more than 5,100 teams in 185 countries — a winner appears to have emerged. The winner will be officially announced this month, and it’s down to two teams.

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This post was written by RichRelevance

ABOUT RichRelevance
RichRelevance is the global leader in experience personalization, driving digital growth and brand loyalty for more than 200 of the world’s largest B2C and B2B brands and retailers. The company leverages advanced AI technologies to bridge the experience gap between marketing and commerce to help digital marketing leaders stage memorable experiences that speak to individuals – at scale, in real time, and across the customer lifecycle. Headquartered in San Francisco, RichRelevance serves clients in 42 countries from 9 offices around the globe.
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