Supervised anomaly detection in uncertain pseudoperiodic data streams
Uncertain data streams have been widely generated in many Web applications. The uncertainty in data streams makes anomaly detection from sensor data streams far more challenging. In this paper, we present a novel framework that supports anomaly detection in uncertain data streams. The proposed frame...
| Main Authors: | , , , , |
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| Format: | Article |
| Published: |
Association for Computing Machinery
2016
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| Online Access: | https://eprints.nottingham.ac.uk/34046/ |