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PErrCas: Process Error Cascade Mining in Trace Streams
Published in ICPM 2021 International Workshops, Eindhoven, The Netherlands, 2022
Efficient and quick detection of problems is an essential task in online process monitoring. Many anomaly detection approaches excel in finding local deviations. We propose a novel approach that tracks local deviations over multiple process instances and visualizes correlations of deviation points. PErrCas provides knowledge about current cascades of deviations to give process analysts a starting point for rational root-cause analysis if processes leave their in-control parameters. PErrCas monitors deviations online and maintains cascades of varying timespans. Hence, our approach avoids defining an observation window beforehand, which is a significant advantage due to its impracticability to predefine expected cascade properties in exploratory scenarios.
Recommended citation: Wimbauer, A., Richter, F., Seidl, T. (2022). PErrCas: Process Error Cascade Mining in Trace Streams. In: Munoz-Gama, J., Lu, X. (eds) Process Mining Workshops. ICPM 2021. Lecture Notes in Business Information Processing, vol 433. Springer, Cham. https://doi.org/10.1007/978-3-030-98581-3_17
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teaching
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Undergraduate course, University 1, Department, 2014
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Teaching experience 2
Workshop, University 1, Department, 2015
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