RECOMMENDING MEDIA ITEMS BASED ON TAKE RATE SIGNALS
    1.
    发明申请
    RECOMMENDING MEDIA ITEMS BASED ON TAKE RATE SIGNALS 有权
    基于采用速率信号的推荐媒体项目

    公开(公告)号:US20150312603A1

    公开(公告)日:2015-10-29

    申请号:US14259784

    申请日:2014-04-23

    Applicant: Netflix, Inc.

    Abstract: In an approach, a method comprises using a server computer in a media content delivery system that is configured to selectively deliver a particular media title from among a library of titles, for a source title, generating title data that specifies an order of a plurality of titles that are related to the source title based on a plurality of stored probability values; wherein each probability value in the plurality of probability values represents, for each particular title of the plurality of titles, a likelihood of selecting the particular title after playing the source title; using the server computer, receiving title impression data, wherein the title impression data specifies a plurality of browsed titles that were browsed from among the plurality of titles but may have not been selected for interaction; using the server computer, receiving title interaction data, wherein the title interaction data specifies a plurality of selected titles that were selected for interaction from the plurality of browsed titles; based on the title interaction data, the title impression data and a statistical model, re-calculating the plurality of probabilities.

    Abstract translation: 在一种方法中,一种方法包括在媒体内容传送系统中使用服务器计算机,该服务器计算机被配置为从源标题库中选择性地传递特定媒体标题,生成指定多个 基于多个存储的概率值与源标题有关的标题; 其中所述多个概率值中的每个概率值对于所述多个标题的每个特定标题表示在播放所述源标题之后选择所述特定标题的可能性; 使用所述服务器计算机,接收标题印象数据,其中所述标题印象数据指定从所述多个标题中浏览的多个浏览标题,但是可能还没有被选择用于交互; 使用所述服务器计算机,接收标题交互数据,其中所述标题交互数据指定从所述多个浏览的标题中选择用于交互的多个所选择的标题; 基于标题交互数据,标题印象数据和统计模型,重新计算多个概率。

    RECOMMENDING MEDIA ITEMS BASED ON TAKE RATE SIGNALS

    公开(公告)号:US20180048925A1

    公开(公告)日:2018-02-15

    申请号:US15791392

    申请日:2017-10-23

    Applicant: NETFLIX, INC.

    Abstract: In an approach, a method comprises using a server computer in a media content delivery system that is configured to selectively deliver a particular media title from among a library of titles, for a source title, generating title data that specifies an order of a plurality of titles that are related to the source title based on a plurality of stored probability values; wherein each probability value in the plurality of probability values represents, for each particular title of the plurality of titles, a likelihood of selecting the particular title after playing the source title; using the server computer, receiving title impression data, wherein the title impression data specifies a plurality of browsed titles that were browsed from among the plurality of titles but may have not been selected for interaction; using the server computer, receiving title interaction data, wherein the title interaction data specifies a plurality of selected titles that were selected for interaction from the plurality of browsed titles; based on the title interaction data, the title impression data and a statistical model, re-calculating the plurality of probabilities.

    RECOMMENDING MEDIA ITEMS BASED ON TAKE RATE SIGNALS

    公开(公告)号:US20160241894A1

    公开(公告)日:2016-08-18

    申请号:US15136846

    申请日:2016-04-22

    Applicant: Netflix, Inc.

    Abstract: In an approach, a method comprises using a server computer in a media content delivery system that is configured to selectively deliver a particular media title from among a library of titles, for a source title, generating title data that specifies an order of a plurality of titles that are related to the source title based on a plurality of stored probability values; wherein each probability value in the plurality of probability values represents, for each particular title of the plurality of titles, a likelihood of selecting the particular title after playing the source title; using the server computer, receiving title impression data, wherein the title impression data specifies a plurality of browsed titles that were browsed from among the plurality of titles but may have not been selected for interaction; using the server computer, receiving title interaction data, wherein the title interaction data specifies a plurality of selected titles that were selected for interaction from the plurality of browsed titles; based on the title interaction data, the title impression data and a statistical model, re-calculating the plurality of probabilities.

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