Discovering High-Level Process Models from Event Logs
https://doi.org/10.18255/1818-1015-2017-2-125-140
Abstract
Process mining is a relatively new field of computer science, which deals with process discovery and analysis based on event logs. In this paper we consider the problem of discovering a high-level business process model from a low-level event log, i.e. automatic synthesis of process models based on the information stored in event logs of information systems. Events in a high-level model are abstract events, which can be refined to low-level subprocesses, whose behavior is recorded in event logs. Models synthesis is intensively studied in the frame of process mining research, but only models and event logs of the same granularity are mainly considered in the literature. Here we present an algorithm for discovering high-level acyclic process models from event logs and some specified partition of low-level events into subsets associated with abstract events in a high-level model.
About the Authors
Antonina A. Begicheva
National Research University Higher School of Economics
Laboratory of Process-Aware Information Systems
Russian Federation
Russian Federation
research assistant
20 Myasnitskaya str., Moscow 101000, Russia
Irina A. Lomazov
National Research University Higher School of Economics
Russian Federation
Russian Federation
Doctor of science, professor
20 Myasnitskaya str., Moscow 101000, Russia
References
1. W. M. P. van der Aalst, Process mining: discovery, conformance and enhancement of business processes, Springer Verlag, 2011.
2. B. F. van Dongen, A. K. A. de Medeiros, H. M. W. Verbeek, A. J. M. M. Weijters, W. M. P. van der Aalst, “The prom framework: A new era in process mining tool support”, International Conference on Application and Theory of Petri Nets, Springer, 2005, 444– 454.
3. W. M. P. van der Aalst, “Verification of workflow nets”, 18th International Conference on Application and Theory of Petri Nets, ICATPN’97, Springer Berlin Heidelberg, Berlin, Heidelberg, 1997, 407–426.
4. S. Smirnov, H. A. Reijers, M. Weske, Th. Nugteren, “Business process model abstraction: a definition, catalog, and survey”, Distributed and Parallel Databases, 30:1 (2012), 63–99.
5. A. Polyvyanyy, S. Smirnov, M. Weske, “Process model abstraction: A slider approach”, Enterprise Distributed Object Computing Conference, 2008 (EDOC’08. 12th International IEEE), IEEE, 2008, 325–331.
6. K. Jensen, L. M. Kristensen, Coloured Petri nets: modelling and validation of concurrent systems, Springer Science & Business Media, 2009.
7. H. J. Genrich, K. Lautenbach, “System modelling with high-level petri nets”, Theoretical computer science, 13:1 (1981), 109–135.
8. W. M. P. van der Aalst, V. Rubin, B. F. van Dongen, E. Kindler, Ch. W. GuЁnther, “Process mining: A two-step approach using transition systems and regions”, BPM Center Report BPM-06-30, BPMcenter. org, 6, 2006.
9. A. J. M. M. Weijters, W. M. P. van der Aalst, A. K. A. De Medeiros, “Process mining with the heuristics miner-algorithm”, Technische Universiteit Eindhoven, Tech. Rep. WP, 166, 2006, 1–34.
10. B. F van Dongen, N. Busi, G. Pinna, W. M. P. van der Aalst, “An iterative algorithm for applying the theory of regions in process mining” (Proceedings of the workshop on formal approaches to business processes and web services (FABPWS’07)), 2007.
11. J. Carmona, J. Cortadella, M. Kishinevsky, “A Region-Based Algorithm for Discovering Petri Nets from Event Logs”, International Conference on Business Process Management, Springer Berlin Heidelberg, Berlin, Heidelberg, 2008, 358–373.
12. W. M. P. van der Aalst, A. K. A. de Medeiros, A. J. M. M. Weijters, “Genetic process mining”, International Conference on Application and Theory of Petri Nets, Springer, 2005, 48–69.
13. A. J. M. M. Weijters, W. M. P. van der Aalst, “Rediscovering workflow models from event- based data using little thumb”, Integrated Computer-Aided Engineering, 10:2 (2003), 151–162.
14. G. Greco, A. Guzzo, L. Pontieri, “Mining taxonomies of process models”, Data & Knowledge Engineering, 67:1 (2008), 74–102.
15. Ch. W. GuЁnther, W. M. P. van der Aalst, “Fuzzy mining–adaptive process simplification based on multi-perspective metrics”, International Conference on Business Process Management, Springer, 2007, 328–343.
16. F. Mannhardt, M. de Leoni, H. A. Reijers, W. M. P. van der Aalst, P. J. Toussaint, “From Low-Level Events to Activities – A Pattern-Based Approach”, Business Process Management: 14th International Conference, BPM 2016, Springer International Publishing, Cham, 2016, 125–141.
17. N. Tax, N. Sidorova, R. Haakma, W. M. P. van der Aalst, “Event abstraction for process mining using supervised learning techniques”, Proceedings of the SAI Conference on Intelligent Systems (IntelliSys), 2016, 161–170.
18. J. Li, R. P. J. Ch. Bose, W. M. P. van der Aalst, “Mining context-dependent and interactive business process maps using execution patterns”, International Conference on Business Process Management, Springer, 2010, 109–121.
19. R. P. J. Ch. Bose, E. H. M. W. Verbeek, W. M. P. van der Aalst, “Discovering hierarchical process models using prom”, Forum at the Conference on Advanced Information Systems Engineering (CAiSE), Springer, 2011, 33–48.
20. J. Cortadella, M. Kishinevsky, A. Kondratyev, L. Lavagno, A. Yakovlev, “Petrify: a tool for manipulating concurrent specifications and synthesis of asynchronous controllers”, IEICE Transactions on information and Systems, 80, 1997, 315–325.
21. A. Kalenkova, I. Lomazova, “Discovery of cancellation regions within process mining techniques”, Fundamenta Informaticae, 133:2–3 (2014), 197–209.
22. A. Kalenkova, I. Lomazova, W. M. P. van der Aalst, “Process Model Discovery: A Method Based on Transition System Decomposition”, International Conference on Application and Theory of Petri Nets, Springer International Publishing, Cham, 2014, 71–90.
23. R. P. J. Chandra Bose, W. M. P. van der Aalst, “Process diagnostics using trace alignment: opportunities, issues, and challenges”, Information Systems, 37:2 (2012), 117–141.
24. Th. Baier, J. Mendling, “Bridging abstraction layers in process mining by automated matching of events and activities”, Business Process Management, Springer, 2013, 17–32.
25. J. Desel, W. Reisig, “The synthesis problem of petri nets”, Acta informatica, 33:4 (1996), 297–315.
26. A. Rozinat, Process mining: conformance and extension, PhD thesis, Technische Universiteit Eindhoven, 2010.
27. A. Begicheva, I. Lomazova, Does your event log fit the high-level process model? Modeling and Analysis of Information Systems, 22:3 (2015), 392–403.
Review
For citations:
Begicheva A.A., Lomazov I.A. Discovering High-Level Process Models from Event Logs. Modeling and Analysis of Information Systems. 2017;24(2):125-140. https://doi.org/10.18255/1818-1015-2017-2-125-140
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