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Keeping our rivers clean: Information-theoretic online anomaly detection for streaming business process events

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References

2014Discovering Block-Structured Process Models from Event Logs Containing Infrequent Behaviour458 cited
2016Scalable process discovery and conformance checking218 cited
2012Algorithms for anomaly detection of traces in logs of process aware information systems118 cited
2018Analyzing business process anomalies using autoencoders112 cited
2017Online conformance checking: relating event streams to process models using prefix-alignments106 cited
2019BINet: Multi-perspective business process anomaly classification96 cited
2015Fast and Accurate Business Process Drift Detection88 cited
2017Event stream-based process discovery using abstract representations81 cited
2019Autoencoders for improving quality of process event logs77 cited
2016Multi-perspective Anomaly Detection in Business Process Execution Events71 cited
2008Outlier Detection Techniques for Process Mining Applications66 cited
2018Online Conformance Checking Using Behavioural Patterns64 cited
2018A Framework for Online Conformance Checking55 cited
2016Detecting Deviating Behaviors Without Models37 cited
2017Multi Instance Anomaly Detection in Business Process Executions

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31 cited

2018Discovering anomalous frequent patterns from partially ordered event logs31 cited

Cited by

2024Survey and Benchmark of Anomaly Detection in Business Processes21 cited
2023WAKE: A Weakly Supervised Business Process Anomaly Detection Framework via a Pre-Trained Autoencoder21 cited