The Netflix Recommender System

By Carlos Alberto Gomez-Uribe, Neil Hunt. ACM Transactions on Management Information Systems, 2015

931 citations recorded by the source corpus.

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Neural Input Search for Large Scale Recommendation Models (2019, neutral): “However, the input component, although contains a great portion of model parameters due to large-sized embeddings, has been frequently designed heuristically across industry, such as YouTube ([7]), Google Play ([6]), Netflix ([9]), etc.”
Sequence-Aware Recommender Systems (2018, background): “Considering the popularity of items within a user community can be important for successful recommendations in practice, e.g., in streaming media recommendation [35].”
EventAction (2019, background): “In addition, commercial recommender systems also quantify user satisfaction with the number of product purchases and returns [22, 39, 41].”
The Architectural Implications of Facebook's DNN-Based Personalized Recommendation (2019, background): “Personalized recommendation is the task of recommending new content to users based on their preferences [21, 24].”
Related Pins at Pinterest: The Evolution of a Real-World Recommender System (2017, background): “Real-world recommender systems have been described for music suggestion [4], image search [12], video discovery on YouTube [2][6][7] and movies on Netflix [9].”