Abstract
The abundance of available event data, originating from process-aware information systems, creates opportunities for enterprise risk management applications at the intersection of the business & management, artificial intelligence and knowledge representation research fields. This paper proposes a rule-based process mining approach for dealing with uncertainty and risk. The applicability of the approach is demonstrated using the updating and debugging process of a social security service provider.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
COSO. Enterprise risk management - integrated framework. Technical report, Committee of Sponsoring Organizations of the Treadway Commission (2004)
Curtis, B., Kellner, M.I., Over, J.: Process modeling. Communications of the ACM 35(9), 75–90 (1992)
Giannakopoulou, D., Havelund, K.: Automata-based verification of temporal properties on running programs. In: Proceedings of the 16th Annual Conference on Automated Software Engineering, pp. 412–416. IEEE Computer Society (2001)
Goedertier, S., Martens, D., Vanthienen, J., Baesens, B.: Robust process discovery with artificial negative events. The Journal of Machine Learning Research 10, 1305–1340 (2009)
Herbst, J.: A machine learning approach to workflow management. In: Lopez de Mantaras, R., Plaza, E. (eds.) ECML 2000. LNCS (LNAI), vol. 1810, pp. 183–194. Springer, Heidelberg (2000)
Pickett, K.H.S.: The Internal Auditing Handbook. Wiley (2010)
Rozinat, A., van der Aalst, W.M.P.: Conformance checking of processes based on monitoring real behavior. Information Systems 33(1), 64–95 (2008)
van der Aalst, W.M.P., de Beer, H.T., van Dongen, B.F.: Process mining and verification of properties: An approach based on temporal logic. In: Meersman, R. (ed.) OTM 2005. LNCS, vol. 3760, pp. 130–147. Springer, Heidelberg (2005)
Van der Aalst, W.M.P., Weijters, T., Maruster, L.: Workflow mining: Discovering process models from event logs. IEEE Transactions on Knowledge and Data Engineering 16(9), 1128–1142 (2004)
Wen, L., Wang, J., Sun, J.: Detecting implicit dependencies between tasks from event logs. In: Zhou, X., Li, J., Shen, H.T., Kitsuregawa, M., Zhang, Y. (eds.) APWeb 2006. LNCS, vol. 3841, pp. 591–603. Springer, Heidelberg (2006)
Yip, F., Wong, A.K.Y., Parameswaran, N., Ray, P.: Rules and ontology in compliance management. In: 11th IEEE International Enterprise Distributed Object Computing Conference, pp. 435–435. IEEE (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Caron, F., Vanthienen, J., Baesens, B. (2012). Rule-Based Business Process Mining: Applications for Management. In: Casillas, J., Martínez-López, F., Corchado Rodríguez, J. (eds) Management Intelligent Systems. Advances in Intelligent Systems and Computing, vol 171. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30864-2_26
Download citation
DOI: https://doi.org/10.1007/978-3-642-30864-2_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-30863-5
Online ISBN: 978-3-642-30864-2
eBook Packages: EngineeringEngineering (R0)