发明名称 Time modulated generative probabilistic models for automated causal discovery using a continuous time noisy-or (CT-NOR) models
摘要 Dependencies between different channels or different services in a client or server may be determined from the observation of the times of the incoming and outgoing of the packets constituting those channels or services. A probabilistic model may be used to formally characterize these dependencies. The probabilistic model may be used to list the dependencies between input packets and output packets of various channels or services, and may be used to establish the expected strength of the causal relationship between the different events surrounding those channels or services. Parameters of the probabilistic model may be either based on prior knowledge, or may be fit using statistical techniques based on observations about the times of the events of interest. Expected times of occurrence between events may be observed, and dependencies may be determined in accordance with the probabilistic model.
申请公布号 US7958069(B2) 申请公布日期 2011.06.07
申请号 US201113007643 申请日期 2011.01.16
申请人 MICROSOFT CORPORATION 发明人 SIMMA ALEKSANDR;GOLDSZMIDT MOISES
分类号 G06E1/00 主分类号 G06E1/00
代理机构 代理人
主权项
地址