Interactive Context-Aware Anomaly Detection Guided by User Feedback

Yang Shi
Yang Shi
Maoran Xu
Maoran Xu
Rongwen Zhao
Rongwen Zhao
Hao Fu
Hao Fu

IEEE Transactions on Human-Machine Systems, pp. 550-559, 2019.

Cited by: 4|Views71
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Abstract:

Automatic anomaly detection techniques have been extensively used to support decision making in abnormal situations. However, existing approaches are limited in their capacity of effectively identifying anomalies due to the complexity of the real-world environment, the uncertainty of the data input, and the unavailability of ground truth....More

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