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    • 45. 发明申请
    • DETECTING COALITION FRAUD IN ONLINE ADVERTISING
    • 检测在线广告中的协商欺诈
    • WO2016191910A1
    • 2016-12-08
    • PCT/CN2015/080220
    • 2015-05-29
    • EXCALIBUR IP, LLC.
    • QIU, Angus XianenXU, HaiyangLIN, Zhangang
    • G06F15/173
    • G06Q30/0248G06Q30/0277
    • Disclosed are methods, systems and computer-readable media, which relate to detecting online coalition fraud. The disclosed method may include grouping visitors that interact with online content into clusters, obtaining traffic features for each visitor, wherein the traffic features are based at least on data representing the corresponding visitor's interaction with the online content; determining, for each cluster, cluster metrics based on (one or more statistical values of) the traffic features of the visitors in that cluster; and determining whether a cluster is fraudulent based on the cluster metrics of the first cluster. For example, determining whether a cluster is fraudulent may include determining whether a first statistical value of the traffic features related to the first cluster is greater than a first threshold value, and/or determining whether a second statistical value of the traffic features related to the first cluster is lower than a second threshold value.
    • 公开了与检测在线联盟欺诈有关的方法,系统和计算机可读介质。 所公开的方法可以包括将与在线内容交互的访问者分组到群集中,为每个访问者获取流量特征,其中流量特征至少基于表示相应访问者与在线内容的交互的数据; 基于(一个或多个统计值)为该群集中的访问者的流量特征确定每个群集的群集度量; 以及基于所述第一集群的集群度量来确定集群是否是欺诈性的。 例如,确定集群是否是欺诈性的可以包括确定与第一集群相关的业务特征的第一统计值是否大于第一阈值,和/或确定与该第一集群相关的业务特征的第二统计值是否 第一簇低于第二阈值。