发明名称 |
LOCALIZED ANOMALY DETECTION USING CONTEXTUAL SIGNALS |
摘要 |
An expected value of a measurement in a first context may be inferred based at least partly on a contextual signal. The contextual signal may comprise an actual value that is: (i) of a same type as the expected value, and (ii) associated with a second context that is different from the first context (e.g., the contexts can comprise geographical areas), or the contextual signal may comprise an actual value that is: (i) of a different type than a type of the expected value, and (ii) associated with the first context, or a second context that is different from the first context. If a difference between the expected value and an actual value of the first context is greater than a threshold difference, this condition is considered an anomaly. A detected anomaly may be used to determine an event that may be significant or otherwise of interest to a user community. |
申请公布号 |
US2017076217(A1) |
申请公布日期 |
2017.03.16 |
申请号 |
US201514856461 |
申请日期 |
2015.09.16 |
申请人 |
Microsoft Technology Licensing, LLC |
发明人 |
Krumm John Charles;Horvitz Eric Joel;Wolk Jessica Kristan |
分类号 |
G06N7/00;G06N99/00 |
主分类号 |
G06N7/00 |
代理机构 |
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代理人 |
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主权项 |
1. A computer-implemented method comprising:
inferring an expected value for a first context based at least in part on a first actual value that is: (i) of a same type as the expected value, and (ii) associated with a second context that is different from the first context; determining a prediction error by comparing the expected value to a second actual value that is: (i) of the same type as the expected value, and (ii) associated with the first context; and determining that an anomaly has occurred in the first context based at least in part on the prediction error. |
地址 |
Redmond WA US |