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    • 1. 发明授权
    • Goal-based video delivery system
    • 基于目标的视频传送系统
    • US08849095B2
    • 2014-09-30
    • US13190714
    • 2011-07-26
    • Nimrod HoofienHarry J. M. RobertsonCaleb E. SpareSean M. Knapp
    • Nimrod HoofienHarry J. M. RobertsonCaleb E. SpareSean M. Knapp
    • H04N9/80H04N21/25H04N21/2543H04N17/00G06Q30/02H04N21/472
    • H04N17/004G06Q30/0241H04N21/251H04N21/25435H04N21/47202
    • A system is provided that facilitates achieving a goal associated with a particular video asset. The system may provide an interface through which a user may specify control parameters that are to be the targets of testing, and a goal or combination of goals. The system may control a controller that performs experiments in an attempt to identify optimal values, relative to the specified goals, for the control parameters. The optimal values may be determined and tested on a per-individual-video asset basis. Further, the controller may generate multiple sets of optimal values for a given video, where each set is associated with a different combination of request attributes. To estimate the optimal parameter values for one video, the controller may use usage information collected for that video, as well as usage information collected for similar videos.
    • 提供了一种有助于实现与特定视频资产相关联的目标的系统。 该系统可以提供一个界面,用户可以通过该界面指定作为测试目标的控制参数,以及目标或目标的组合。 系统可以控制执行实验的控制器,以试图相对于控制参数的指定目标来识别最佳值。 可以基于每个个人视频资产确定和测试最佳值。 此外,控制器可以为给定视频生成多组最优值,其中每个集合与请求属性的不同组合相关联。 为了估计一个视频的最佳参数值,控制器可以使用为该视频收集的使用信息,以及为类似视频收集的使用信息。
    • 4. 发明授权
    • Automatically recommending content
    • 自动推荐内容
    • US08260117B1
    • 2012-09-04
    • US13401098
    • 2012-02-21
    • Zhichen XuSami Abu-El-HaijaLei HuangNimrod Hoofien
    • Zhichen XuSami Abu-El-HaijaLei HuangNimrod Hoofien
    • H04N9/80
    • H04N21/4668
    • Techniques are provided for selecting which videos to recommend to users by predicting the degree to which recommending each video will satisfy certain goals. To make the predictions, a trained machine learning engine is fed both collaborative filtering parameter values and content-based filtering parameter values. In the case of video-to-video recommendations, the collaborative filtering parameter values may be based on a video pair that includes a video in which a user has already demonstrated an interest. The machine learning engine generates a machine-learning score for each video. The machine learning scores are used as the basis for selecting which videos to recommend to a particular user.
    • 提供技术来通过预测推荐每个视频满足某些目标的程度来选择要向用户推荐哪些视频。 为了做出预测,训练有素的机器学习引擎提供协同过滤参数值和基于内容的过滤参数值。 在视频到视频推荐的情况下,协作过滤参数值可以基于包括用户已经表现出兴趣的视频的视频对。 机器学习引擎为每个视频生成机器学习分数。 机器学习分数被用作选择哪些视频推荐给特定用户的基础。