MACHINE LEARNING TECHNIQUES FOR GENERATING ENJOYMENT SIGNALS FOR WEIGHTING TRAINING DATA

    公开(公告)号:US20220180186A1

    公开(公告)日:2022-06-09

    申请号:US17192515

    申请日:2021-03-04

    Applicant: NETFLIX, INC.

    Abstract: Various embodiments set forth systems and techniques for training a personalized prediction model. The techniques include generating, based on interaction data associated with one or more users and a first weight associated with the interaction data, a first set of training data; generating, based on the personalized prediction model, a predicted enjoyment signal associated with playback of a digital content item; generating, based on the first set of training data and the predicted enjoyment signal, a second set of training data; and updating one or more parameters of a personalized ranking model based on the second set of training data.

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    发明申请

    公开(公告)号:US20220334951A1

    公开(公告)日:2022-10-20

    申请号:US17853648

    申请日:2022-06-29

    Applicant: Netflix, Inc.

    Abstract: The disclosed computer-implemented method may include accessing updated data structures that are to be included in a user interface functionality test, where the updated data structures contribute to a user interface. The method may also include accessing live or snapshotted data captured from services running in a production environment, initiating generation of a first user interface instance using the updated data structures and using the accessed live or snapshotted data, and initiating generation of a second user interface instance using a different version of the data structures and using the same accessed live or snapshotted data. The method further includes comparing the first user interface instance to the second user interface instance to identify differences and then determine which outcome-defining effects the updated data structures had on the user interface based on the identified differences between the user interfaces. Various other methods, systems, and computer-readable media are also disclosed.

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