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Home/Magazine Archive/November 2016 (Vol. 59, No. 11)/Recommender Systems: Beyond Matrix Completion/Abstract

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Recommender Systems: Beyond Matrix Completion

By Dietmar Jannach, Paul Resnick, Alexander Tuzhilin, Markus Zanker
Communications of the ACM, November 2016, Vol. 59 No. 11, Pages 94-102
10.1145/2891406
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Recommender Systems Beyond Matrix Completion, illustration — Credit: Alicia Kubista / Andrij Borys Associates

The use of recommender systems has exploded over the last decade, making personalized recommendations ubiquitous online. Most of the major companies, including Google, Facebook, Twitter, LinkedIn, Netflix, Amazon, Microsoft, Yahoo!, eBay, Pandora, Spotify, and many others use recommender systems (RS) within their services.

Key Insights

These systems are used to recommend a whole range of items, including consumer products, movies, songs, friends, news articles, restaurants and various others. Recommender systems constitute a mission-critical technology in several companies. For example, Netflix reports that at least 75% of its downloads and rentals come from their RS, thus making it of strategic importance to the company.^a

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