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Outlier Detection Techniques for Process Mining Applications

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References

2003Workflow mining: A survey of issues and approaches1,052 cited
2006Discovering expressive process models by clustering log traces321 cited
2006A Rule-Based Approach for Process Discovery: Dealing with Noise and Imbalance in Process Logs95 cited
2005Mining of ad-hoc business processes with TeamLog87 cited

Cited by

2018Discovering more precise process models from event logs by filtering out chaotic activities66 cited
2015Discovering deviating cases and process variants using trace clustering53 cited
2016Detecting Deviating Behaviors Without Models37 cited
2013Wanna improve process mining results? : it’s high time we consider data quality issues seriously34 cited
2018Mining frequent patterns in process models33 cited
2020Detecting anomalies in business process event logs using statistical leverage29 cited
2021Detecting temporal workarounds in business processes – A deep-learning-based method for analysing event log data28 cited
2020Automatic Repair of Same-Timestamp Errors in Business Process Event Logs27 cited
2011Region-Based Foldings in Process Discovery26 cited
2022Advanced Process Discovery Techniques25 cited
2011

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Projection approaches to process mining using region-based techniques

25 cited

2022Action-oriented process mining: bridging the gap between insights and actions24 cited

2017A framework for detecting deviations in complex event logs23 cited

2021Keeping our rivers clean: Information-theoretic online anomaly detection for streaming business process events22 cited

2022Demystifying Noise and Outliers in Event Logs: Review and Future Directions19 cited

2019Measuring the Behavioral Quality of Log Sampling19 cited