Anomaly pattern detection for streaming data
作者：
Highlights：
• We propose an anomaly pattern detection method for streaming data.
• It detects a point where the pattern is unusually different from normal behavior.
• A data stream is transformed into a stream of binary values indicating outliers.
• An anomaly pattern on a stream of binary values is detected by two approaches.
• The proposed method is not sensitive to the performance of outlier detection method.
摘要
•We propose an anomaly pattern detection method for streaming data.•It detects a point where the pattern is unusually different from normal behavior.•A data stream is transformed into a stream of binary values indicating outliers.•An anomaly pattern on a stream of binary values is detected by two approaches.•The proposed method is not sensitive to the performance of outlier detection method.
论文关键词：Anomaly pattern detection,Control charts,Hypothesis testing,Outlier detection,Streaming data
论文评审过程：Received 14 March 2019, Revised 6 December 2019, Accepted 28 January 2020, Available online 8 February 2020, Version of Record 19 February 2020.
论文官网地址：https://doi.org/10.1016/j.eswa.2020.113252
