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A framework for steady-state detection in process mining

delete2026-04-20
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PRE
AI
A
Alexander Kraus *
K
Keyvan Amiri Elyasi
A
Adrian Rebmann
S
Sherri Hadian
H
Han van der Aa
DOI：10.1016/j.is.2026.102740delete
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Abstract

Abstract

En 中文
• Introduces steady-state detection as a new research problem in process mining. • Presents a data-driven framework for identifying steady states in business processes. • Provides an accuracy evaluation of the framework using synthetic event logs. • Demonstrates the effect of steady-state detection on key process mining tasks using real-life data.
Keywords:
steady-state detection
process mining
data-driven framework
business processes
accuracy evaluation

Journal

I
Information Systems
IF:
3.4
Papers:
134
Citations:
0

Organization

U
University of Mannheim
Scholars:
1.9K
Papers: 2.2K
Citations: 3.2K
S
sap se
Scholars:
5
Papers: 3
Citations: 0
U
University of Vienna
Scholars:
1.7W
Papers: 1.6W
Citations: 40
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