Implementing and maintaining feedback loops in recommendation systems
AssigneeNetflix, Inc.
InventorsDing Tong, Qifeng Qiao, Justin Derrick Basilico, Ting-Po Lee, James McInerney
Life of this patent
Estimating the term…
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AssigneeNetflix, Inc.
InventorsDing Tong, Qifeng Qiao, Justin Derrick Basilico, Ting-Po Lee, James McInerney
Estimating the term…
A computer-implemented method includes identifying offline evaluation metrics that indicate, for a given feedback loop in a recommendation system, various feedback loop characteristics that are detrimental to the feedback loop. The method also includes generating a predictive machine learning (ML) model that correlates the identified offline evaluation metrics with indications of those feedback loop characteristics that are detrimental to the feedback loop. The method further includes instantiating the predictive ML model to predict, using the correlated offline evaluation metrics and the detrimental feedback loop characteristics, how the feedback loop will be negatively affected over time, and providing, to at least one entity, an indication of how the feedback loop will be negatively affected over time due to the detrimental feedback loop characteristics. Various other methods, systems, and computer-readable media are also disclosed.
A computer-implemented method comprising:
A system comprising:
A non-transitory computer-readable medium comprising one or more computer-executable instructions that, when executed by at least one processor of a computing device, cause the computing device to:
Dependencies are inferred from the claim text.