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    • 1. 发明授权
    • Node clustering
    • 节点集群
    • US08572239B2
    • 2013-10-29
    • US12885897
    • 2010-09-20
    • Fei CaoShaoyu ZhouZhuoqing Wu, Jr.Sijian ZhangSiddhartha RoyMichael A. Elizarov
    • Fei CaoShaoyu ZhouZhuoqing Wu, Jr.Sijian ZhangSiddhartha RoyMichael A. Elizarov
    • G06F15/177G06F15/16
    • G06Q30/02G06Q30/0201
    • Large sets of unorganized data may provide little value in identifying useful observations from such data. For example, an online merchant may maintain a database of millions of user IDs (e.g., a cookie ID, a login ID, a device ID, a network ID, etc.) along with content viewed and/or actions taken with the user IDs, where minimal associations are known between user IDs. It may be advantageous to link together user IDs of respective users to capture a comprehensive view of respective users' activities. Accordingly, one or more systems and/or techniques for identifying a cluster of nodes based upon transforming a set of node pairings (e.g., pairings of related nodes) one or more times are disclosed herein. Iterative transformations may be performed until respective nodes are paired with merely their smallest neighboring node and are paired with no other node. In this way, node clusters may be identifiable.
    • 大量无组织数据可能无法从这些数据中识别有用的观察结果。 例如,在线商家可以维护数百万用户ID的数据库(例如,Cookie ID,登录ID,设备ID,网络ID等)以及与用户ID一起观看的内容和/或所采取的动作 其中用户ID之间的最小关联是已知的。 链接各个用户的用户ID可能是有利的,以捕获各个用户的活动的综合视图。 因此,本文公开了一种或多种用于基于将一组节点配对(例如,相关节点的配对)一次或多次来识别节点簇的一个或多个系统和/或技术。 可以执行迭代变换,直到各个节点仅与其最小的相邻节点配对并且与没有其他节点配对。 以这种方式,节点集群可以是可识别的。
    • 3. 发明申请
    • NODE CLUSTERING
    • 节点聚类
    • US20120072554A1
    • 2012-03-22
    • US12885897
    • 2010-09-20
    • Fei CaoShaoyu ZhouZhuoqing WuSijian ZhangSiddhartha RoyMichael A. Elizarov
    • Fei CaoShaoyu ZhouZhuoqing WuSijian ZhangSiddhartha RoyMichael A. Elizarov
    • G06F15/177G06F15/16
    • G06Q30/02G06Q30/0201
    • Large sets of unorganized data may provide little value in identifying useful observations from such data. For example, an online merchant may maintain a database of millions of user IDs (e.g., a cookie ID, a login ID, a device ID, a network ID, etc.) along with content viewed and/or actions taken with the user IDs, where minimal associations are known between user IDs. It may be advantageous to link together user IDs of respective users to capture a comprehensive view of respective users' activities. Accordingly, one or more systems and/or techniques for identifying a cluster of nodes based upon transforming a set of node pairings (e.g., pairings of related nodes) one or more times are disclosed herein. Iterative transformations may be performed until respective nodes are paired with merely their smallest neighboring node and are paired with no other node. In this way, node clusters may be identifiable.
    • 大量无组织数据可能无法从这些数据中识别有用的观察结果。 例如,在线商家可以维护数百万用户ID的数据库(例如,Cookie ID,登录ID,设备ID,网络ID等)以及与用户ID一起观看的内容和/或所采取的动作 其中用户ID之间的最小关联是已知的。 链接各个用户的用户ID可能是有利的,以捕获各个用户的活动的综合视图。 因此,本文公开了一种或多种用于基于将一组节点配对(例如,相关节点的配对)一次或多次来识别节点簇的一个或多个系统和/或技术。 可以执行迭代变换,直到各个节点仅与其最小的相邻节点配对并且与没有其他节点配对。 以这种方式,节点集群可以是可识别的。