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    REINFORCEMENT LEARNING FOR GUARANTEED DELIVERY OF SUPPLEMENTAL CONTENT
    3.
    发明申请
    REINFORCEMENT LEARNING FOR GUARANTEED DELIVERY OF SUPPLEMENTAL CONTENT 有权

    公开(公告)号：US20220360854A1

    公开(公告)日：2022-11-10

    申请号：US17315107

    申请日：2021-05-07

    申请人： HULU, LLC

    发明人： Pengfei Gao ,  Dingming Wu ,  Chunyang Wei ,  Xiaohui Xie ,  Shulei Ma

    IPC分类号： H04N21/472 ,  H04N21/45 ,  H04N21/442 ,  H04N21/466 ,  G06Q30/02 ,  G06N20/00 ,  G06N5/04

    摘要： In some embodiments, a method receives a request for supplemental content to be provided in association with main content. The method selects an instance of supplemental content based on a long-term reward metric and a short-term reward metric. The long-term reward metric is based on feedback from delivery of a plurality of instances of supplemental content and a delivery status for a delivery constraint of one instance of supplemental content. The short-term reward metric is based on feedback from delivery of the one instance of supplemental content. The long-term reward metric is based on feedback from delivery of a plurality of instances of supplemental content and the short-term reward metric is based on feedback from delivery of one instance of supplemental content. The instance of supplemental content is provided to a client device.

    Reinforcement learning for guaranteed delivery of supplemental content
    4.
    发明授权
    Reinforcement learning for guaranteed delivery of supplemental content 有权

    公开(公告)号：US11546665B2

    公开(公告)日：2023-01-03

    申请号：US17315107

    申请日：2021-05-07

    申请人： HULU, LLC

    发明人： Pengfei Gao ,  Dingming Wu ,  Chunyang Wei ,  Xiaohui Xie ,  Shulei Ma

    IPC分类号： H04N21/442 ,  H04N21/472 ,  H04N21/45 ,  G06N5/04 ,  H04N21/466 ,  G06Q30/02 ,  G06N20/00

    摘要： In some embodiments, a method receives a request for supplemental content to be provided in association with main content. The method selects an instance of supplemental content based on a long-term reward metric and a short-term reward metric. The long-term reward metric is based on feedback from delivery of a plurality of instances of supplemental content and a delivery status for a delivery constraint of one instance of supplemental content. The short-term reward metric is based on feedback from delivery of the one instance of supplemental content. The long-term reward metric is based on feedback from delivery of a plurality of instances of supplemental content and the short-term reward metric is based on feedback from delivery of one instance of supplemental content. The instance of supplemental content is provided to a client device.

    Optimal supplemental content selection in content delivery
    5.
    发明授权
    Optimal supplemental content selection in content delivery 有权

    公开(公告)号：US11849188B2

    公开(公告)日：2023-12-19

    申请号：US17653422

    申请日：2022-03-03

    申请人： HULU, LLC

    发明人： Dingming Wu ,  Chunyang Wei ,  Changsheng Xiang ,  Shulei Ma

    IPC分类号： H04N21/4722 ,  H04N21/266 ,  H04N21/472

    CPC分类号： H04N21/4722 ,  H04N21/266 ,  H04N21/47202

    摘要： In some embodiments, a method receives information for a delivery of instances of supplemental content for a plurality of line items. A line item is associated with an instance of supplemental content that can be delivered and a pacing curve that describes a pace of delivery over time. The method updates a parameter for the line item to generate an updated parameter based on the delivery of the instances of supplemental content and a desired pacing behavior. The updated parameter is provided to a selection system that uses the updated parameter to select an instance for delivery. The delivery of instances of supplemental content for the line item is adjusted to meet the pacing curve based on a characteristic of the pacing behavior.

    Account behavior prediction using prediction network
    6.
    发明授权
    Account behavior prediction using prediction network 有权

    公开(公告)号：US11601718B2

    公开(公告)日：2023-03-07

    申请号：US17335400

    申请日：2021-06-01

    申请人： HULU, LLC

    发明人： Qingying Chen ,  Shulei Ma ,  Chunyang Wei

    IPC分类号： H04H60/56 ,  H04N21/466 ,  H04N21/45 ,  H04N21/442

    摘要： In some embodiments, a method inputs a sequence of historical behaviors for a plurality of instances of content into a prediction network to generate a sequence of values that model the sequence of historical behaviors. A restriction on an operation performed by the prediction network is based on a characteristic of an viewing behavior. A sequence of attention scores is generated based on a similarity of a current behavior for a first instance of content to respective instances of historical behaviors in the sequence of historical behaviors. The method adjusts respective values based on corresponding attention scores to generate an adjusted sequence of values. The adjusted sequence of features are sampled to generate an output from the prediction network that models the sequence of historical behaviors based on the current behavior. The output for determining a prediction if the current behavior is indicative of the viewing behavior.