Mining association rules for anomaly detection in dynamic process runtime behavior and explaining the root cause to users
作者：
Highlights：
• Visualization concepts for rule violations, anomalies, and root causes are presented.
• A comparison with five alternative anomaly detection approaches is given.
• Related design requirements are discussed based on systematic literature reviews.
• A user study on process anomaly root cause visualization techniques is performed.
• Related challenges and limitations are discussed.
摘要
•Visualization concepts for rule violations, anomalies, and root causes are presented.•A comparison with five alternative anomaly detection approaches is given.•Related design requirements are discussed based on systematic literature reviews.•A user study on process anomaly root cause visualization techniques is performed.•Related challenges and limitations are discussed.
论文关键词：Anomaly detection,Process runtime behavior,Root cause,Association rule mining,Process change
论文评审过程：Received 1 February 2019, Revised 1 June 2019, Accepted 10 September 2019, Available online 18 September 2019, Version of Record 17 March 2020.
论文官网地址：https://doi.org/10.1016/j.is.2019.101438
