Guest Talk: Checking Process Compliance on the Basis of Uncertain Event-to-Activity Mappings
Henrik Leopold, PhD
Date/Time: 12.07.2017, 12:00
A crucial requirement for compliance-checking techniques is that observed behavior, captured in event traces, can be mapped to the process models that specify allowed behavior. Without a mapping, it is not possible to determine if observed behavior is compliant or not. A considerable problem in this regard is that establishing a mapping between events and process model activities is an inherently uncertain task. Since the use of a particular mapping directly influences the compliance of a trace to a specification, this uncertainty represents a major issue for compliance checking. To overcome this issue, we introduce a probabilistic compliance-checking method that can deal with uncertain mappings. Our method avoids the need to select a single mapping, but rather works on a spectrum of possible mappings. A quantitative evaluation demonstrates that our method can be applied on a considerable number of real-world processes where traditional compliance-checking methods fail.
Henrik Leopold is an Assistant Professor at the Department of Computer Science at the VU University Amsterdam. He received a PhD degree (Dr. rer. pol.) as well as a master degree in information systems from the Humboldt University Berlin. His doctoral thesis on Natural Language in Business Process Models received the TARGION Dissertation Award for the best doctoral thesis in the field of Information Management between 2012 and 2014. From July 2013 to March 2014 he worked as a postdoctoral research fellow at the Humboldt University Berlin. Afterwards, he joined WU Vienna as an Assistant Professor from April 2014 to January 2015. He has been a visiting researcher at the Eindhoven University of Technology, the Universidade Federal do Estado do Rio de Janeiro, and the University of Mannheim. His current research interests relate to the combination of Business Process Management with Natural Language Processing and Artificial Intelligence techniques. The results of his research have been published, among others, in Data & Knowledge Engineering, Decision Support Systems, IEEE Software, IEEE Transactions on Software Engineering, the Journal of Systems and Software, and Information Systems.
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