Using process mining to learn from process changes in evolutionary systems Online publication date: Tue, 08-Jul-2008
by Christian W. Gunther, Stefanie Rinderle-Ma, Manfred Reichert, Wil M.P. Van Der Aalst, Jan Recker
International Journal of Business Process Integration and Management (IJBPIM), Vol. 3, No. 1, 2008
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.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Business Process Integration and Management (IJBPIM):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook