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Netflix Creates Local Recommendations Using Global Communities
The algorithm wizards at Netflix pull back the curtain and show how they use worldwide data to improve local and personal recommendations.

As the first global video network, Netflix needs to conquer problems no one else has had to face. Yesterday, the subscription video-on-demand leader published a pair of blog posts about how it's creating recommendations for a worldwide audience.

The posts make for fascinating reading. Netflix is now in 190 countries, but the subscriber base in many counties is too small to create useful local recommendations. Netflix overcomes this by studying worldwide groups of viewers with the same niche tastes. One of the posts shows how viewers who enjoy a particular style of anime or health-conscious food videos tend to have similar tastes no matter what country they're in. By creating these global affinity groups, Netflix is able to offer more useful recommendations.

The complications of global rights presents Netflix with another challenge to overcome: Since not all titles are available in all countries, the recommendation system could easily overestimate the popularity of content that's widely available. By understanding local availability, Netflix is able to getter a truer measure of a title's popularity. Studying worldwide patterns lets Netflix deliver better recommendations when a title is first introduced to a country. Netflix also needed to understand how local tastes and different languages (it now supports 21 languages) impact video preferences.

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