Abstract
Process discovery—discovering a process model from example behavior recorded in an event log—is one of the most challenging tasks in process mining. The primary reason is that conventional modeling languages (e.g., Petri nets, BPMN, EPCs, and ULM ADs) have difficulties representing the observed behavior properly and/or succinctly. Moreover, discovered process models tend to have deadlocks and livelocks. Therefore, we advocate a new representation more suitable for process discovery: causal nets. Causal nets are related to the representations used by several process discovery techniques (e.g., heuristic mining, fuzzy mining, and genetic mining). However, unlike existing approaches, we provide declarative semantics more suitable for process mining. To clarify these semantics and to illustrate the non-local nature of this new representation, we relate causal nets to Petri nets.
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References
van der Aalst, W.M.P.: The Application of Petri Nets to Workflow Management. The Journal of Circuits, Systems and Computers 8(1), 21–66 (1998)
van der Aalst, W.M.P.: Process Mining: Discovery, Conformance and Enhancement of Business Processes. Springer, Berlin (2011)
van der Aalst, W.M.P., van Hee, K.M., ter Hofstede, A.H.M., Sidorova, N., Verbeek, H.M.W., Voorhoeve, M., Wynn, M.T.: Soundness of Workflow Nets: Classification, Decidability, and Analysis. Formal Aspects of Computing 23(3), 333–363 (2011)
Adriansyah, A., van Dongen, B.F., van der Aalst, W.M.P.: Towards Robust Conformance Checking. In: Muehlen, M.z., Su, J. (eds.) BPM 2010. LNBIP, vol. 66, pp. 122–133. Springer, Heidelberg (2011)
Bruni, R., Montanari, U.: Zero-Safe Nets: Comparing the Collective and Individual Token Approaches. Information and Computation 156(1-2), 46–89 (2000)
Dehnert, J., van der Aalst, W.M.P.: Bridging the Gap Between Business Models and Workflow Specifications. International Journal of Cooperative Information Systems 13(3), 289–332 (2004)
Günther, C.W., van der Aalst, W.M.P.: Fuzzy Mining – Adaptive Process Simplification Based on Multi-perspective Metrics. In: Alonso, G., Dadam, P., Rosemann, M. (eds.) BPM 2007. LNCS, vol. 4714, pp. 328–343. Springer, Heidelberg (2007)
Alves de Medeiros, A.K., Weijters, A.J.M.M., van der Aalst, W.M.P.: Genetic Process Mining: An Experimental Evaluation. Data Mining and Knowledge Discovery 14(2), 245–304 (2007)
Weijters, A.J.M.M., van der Aalst, W.M.P.: Rediscovering Workflow Models from Event-Based Data using Little Thumb. Integrated Computer-Aided Engineering 10(2), 151–162 (2003)
Weijters, A.J.M.M., Ribeiro, J.T.S.: Flexible Heuristics Miner (FHM). BETA Working Paper Series, WP 334. Eindhoven University of Technology, Eindhoven (2010)
van der Werf, J.M.E.M., van Dongen, B.F., Hurkens, C.A.J., Serebrenik, A.: Process Discovery using Integer Linear Programming. Fundamenta Informaticae 94, 387–412 (2010)
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van der Aalst, W., Adriansyah, A., van Dongen, B. (2011). Causal Nets: A Modeling Language Tailored towards Process Discovery. In: Katoen, JP., König, B. (eds) CONCUR 2011 – Concurrency Theory. CONCUR 2011. Lecture Notes in Computer Science, vol 6901. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23217-6_3
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DOI: https://doi.org/10.1007/978-3-642-23217-6_3
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