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    • 25. 发明申请
    • FAST BEHAVIOR AND ABNORMALITY DETECTION
    • 快速行为和异常检测
    • WO2016081946A1
    • 2016-05-26
    • PCT/US2015/062204
    • 2015-11-23
    • THE REGENTS OF THE UNIVERSITY OF CALIFORNIA
    • SARRAFZADEH, MajidDABIRI, FoadNOSHADI, Hyduke
    • G06Q50/10
    • G06K9/00348G06K9/469G06N99/005
    • A system includes an interface configured to receive time series data representing information from a plurality of sensors, and a processor configured to construct a behavior model based on the time series data. The processor identifies features in the time series data, divides the time series data of each of the identified features into segments, and extracts feature components from the segments. The processor further constructs a plurality of state graphs, each state graph including components connected by weighted edges, constructs a behavior graph, wherein the state graphs form vertices of the behavior graph, clusters the state graphs in the behavior graph; and selects a representative state graph from each cluster, wherein the behavior model includes the selected state graphs.
    • 系统包括被配置为接收表示来自多个传感器的信息的时间序列数据的接口,以及被配置为基于时间序列数据构建行为模型的处理器。 处理器识别时间序列数据中的特征,将每个识别的特征的时间序列数据划分成段,并从段中提取特征成分。 处理器还构造多个状态图,每个状态图包括通过加权边缘连接的组件,构建行为图,其中状态图形成行为图的顶点,聚集行为图中的状态图; 并且从每个集群中选择代表状态图,其中所述行为模型包括所选择的状态图。