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Description Netflix's mantra is "connecting people to the movies they love." To help customers find those movies, Netflix developed a world-class movie recommendation system: Cinematch. Its job being to predict whether someone will enjoy a movie based on how much they liked or disliked other movies using those predictions to make personal movie recommendations based on each customer’s unique tastes. While Cinematch was doing pretty well, Netfix established the Netflix Prize to reward an individual or a team to the tune of $1m for bettering Netflix's own recommendation algorithms.
Location United States of America
Editor's comments The Netflix Prize was a landmark example of how a corporation established a crowdsourcing competition platform to openly source improvements for one of its core assets and competitive differentiators, its recommendation algorithms.

Netflix provided participants with a lot of anonymous rating data, and a prediction accuracy bar that is 10% better than what Cinematch can do on the same training data set (Accuracy being a measurement of how closely predicted ratings of movies match subsequent actual ratings). any individual or team that develops a system that beats the bar was awarded serious money and bragging rights!

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