A Survey on Concept Drift in Process Mining
It addresses the challenge of evolving processes in process mining for researchers and practitioners, but is incremental as a literature review.
This survey paper systematically reviews concept drift in process mining, identifying that current methods primarily focus on offline analysis and lack standardized evaluation protocols, datasets, and metrics.
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.