Title: Using process mining to learn from process changes in evolutionary systems

Authors: Christian W. Gunther, Stefanie Rinderle-Ma, Manfred Reichert, Wil M.P. Van Der Aalst, Jan Recker

Addresses: Eindhoven University of Technology, The Netherlands. ' Department of Databases and Information Systems, University of Ulm, Germany. ' University of Twente, The Netherlands. ' Department of Mathematics and Computer Science, Eindhoven University of Technology, The Netherlands. ' Queensland University of Technology, Brisbane, Queensland, Australia

Abstract: Traditional information systems struggle with the requirement to provide flexibility and process support while still enforcing some degree of control. Accordingly, adaptive Process Management Systems (PMSs) have emerged that provide some flexibility by enabling dynamic process changes during runtime. Based on the assumption that these process changes are recorded explicitly, we present two techniques for mining change logs in adaptive PMSs; that is, we do not only analyse the execution logs of the operational processes, but also consider the adaptations made at the process instance level. The change processes discovered through process mining provide an aggregated overview of all changes that happened so far. Using process mining as an analysis tool we show in this paper how better support can be provided for truly flexible processes by understanding when and why process changes become necessary.

Keywords: process awareness; information systems; process mining; change mining; process changes; process management; flexibility; dynamic processes; flexible processes.

DOI: 10.1504/IJBPIM.2008.019348

International Journal of Business Process Integration and Management, 2008 Vol.3 No.1, pp.61 - 78

Published online: 08 Jul 2008 *

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