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    • 74. 发明授权
    • Handling crowd requests for large geographic areas
    • 处理大地理区域的人群要求
    • US08321509B2
    • 2012-11-27
    • US12645560
    • 2009-12-23
    • Kenneth JenningsChristopher M. AmidonRavi Reddy Katpelly
    • Kenneth JenningsChristopher M. AmidonRavi Reddy Katpelly
    • G06F15/16
    • H04L41/0893G06F21/6227G06Q10/10G06Q30/02H04L67/18H04L67/22H04L67/24H04L67/306H04W4/02H04W4/021H04W4/029H04W64/00
    • A system and method are provided for processing a request for crowd data for a large geographic area. In one embodiment, a central system, which includes one or more servers, operates to obtain current locations for users of mobile devices and form crowds of three or more users based on the current locations of the users. In order to provide access to crowd data for crowds for a large geographic area, the central system receives a request for crowd data from a requesting device, establishes a bounding region for the request, and identifies one or more starting points within the bounding region for the request. Crowds are identified, crowd data for the crowds is generated, and the crowd data is returned to the requesting device in an iterative manner for a series of two or more outwardly radiating, concentric geographic regions centered at the one or more starting points.
    • 提供了一种系统和方法,用于处理针对大地理区域的人群数据的请求。 在一个实施例中,包括一个或多个服务器的中央系统操作以获得移动设备的用户的当前位置,并且基于用户的当前位置来形成三个或更多个用户的群体。 为了提供访问用于大地理区域的人群的人群数据,中央系统从请求设备接收到人群数据的请求,为请求建立边界区域,并且识别边界区域内的一个或多个起点 请求。 识别人群,生成人群的人群数据,并且以迭代的方式将人群数据返回给请求设备,用于一系列两个或更多个以一个或多个起始点为中心的向外辐射,同心的地理区域。
    • 77. 发明申请
    • SMART ENCOUNTERS
    • US20120047087A1
    • 2012-02-23
    • US12711517
    • 2010-02-24
    • Christopher M. AmidonSteven L. Petersen
    • Christopher M. AmidonSteven L. Petersen
    • G06Q99/00G06Q50/00G06N5/02
    • G01C21/34G01C21/00G06N5/04G06Q30/0282H04W4/029H04W12/02
    • Systems and methods for providing content recommendations to a user based on aggregate profile data of other users that the user is predicted to encounter in the future are disclosed. In general, an aggregate profile is obtained for a predicted encounter of a first user. The aggregate profile is based on user profiles of a number of second users identified for the predicted encounter. In one embodiment, the predicted encounter is a predicted physical encounter. In another embodiment, the predicted encounter is a predicted remote encounter. One or more content recommendations are then obtained for the first user based on the aggregate profile for the predicted encounter. The content recommendation may be, for example, a recommended movie, a recommended television program, a recommended news article, a recommended user-generated video (e.g., a recommended video on YouTube.com), or the like.
    • 公开了基于用户将来会遇到的其他用户的聚合简档数据向用户提供内容推荐的系统和方法。 通常,获得针对第一用户的预测遇到的聚集简档。 聚合配置文件基于为预测的遭遇而识别的多个第二用户的用户简档。 在一个实施例中,预测的相遇是预测的物理遭遇。 在另一个实施例中,预测的相遇是预测的远程遭遇。 然后,基于预测的遭遇的聚合简档,为第一用户获得一个或多个内容建议。 内容推荐可以是例如推荐的电影,推荐的电视节目,推荐的新闻文章,推荐的用户生成的视频(例如,YouTube.com上的推荐视频)等。