A Survey on Concept Drift in Process Mining
- URL: http://arxiv.org/abs/2112.02000v1
- Date: Fri, 3 Dec 2021 16:28:44 GMT
- Title: A Survey on Concept Drift in Process Mining
- Authors: Denise Maria Vecino Sato, Sheila Cristiana de Freitas, Jean Paul
Barddal and Edson Emilio Scalabrin
- Abstract summary: Concept drift in process mining (PM) is a challenge as classical methods assume processes are in a steady-state, i.e., events share the same process version.
Existing works depict that (i) PM still primarily focuses on offline analysis, and (ii) the assessment of concept drift techniques in processes is cumbersome due to the lack of common evaluation protocol, datasets, and metrics.
- Score: 2.8617826964327113
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Concept drift in process mining (PM) is a challenge as classical methods
assume processes are in a steady-state, i.e., events share the same process
version. We conducted a systematic literature review on the intersection of
these areas, and thus, we review concept drift in process mining and bring
forward a taxonomy of existing techniques for drift detection and online
process mining for evolving environments. Existing works depict that (i) PM
still primarily focuses on offline analysis, and (ii) the assessment of concept
drift techniques in processes is cumbersome due to the lack of common
evaluation protocol, datasets, and metrics.
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