On Process Model Synthesis Based on Event Logs with Noise
https://doi.org/10.18255/1818-1015-2014-4-181-198
Abstract
Process mining is a new emerging discipline related to process management, formal process models, and data mining. One of the main tasks of process mining is the model synthesis (discovery) based on event logs. A wide range of algorithms for process model discovery, analysis, and enhancement is developed. The real-life event logs often contain noise of different types. In this paper we describe the main causes of noise in the event logs and study the effect of noise on the performance of process discovery algorithms. The experimental results of application of the main process discovery algorithms to artificial event logs with noise are provided. Specially generated event logs with noise of different types were processed using the four basic discovery techniques. Although modern algorithms can cope with some types of noise, in most cases, their use does not lead to obtaining a satisfactory result. Thus, there is a need for more sophisticated algorithms to deal with noise of different types.
About the Authors
A. A. Mitsyuk
National Research University Higher School of Economics
Russian Federation
аналитик, International laboratory of process-aware information systems, Kochnovskiy Proezd, 3, Moscow, 125319, Russia
Russian Federation
аналитик, International laboratory of process-aware information systems, Kochnovskiy Proezd, 3, Moscow, 125319, Russia
I. S. Shugurov
National Research University Higher School of Economics
Russian Federation
стажер-исследователь, International laboratory of process-aware information systems, Kochnovskiy Proezd, 3, Moscow, 125319, Russia
Russian Federation
стажер-исследователь, International laboratory of process-aware information systems, Kochnovskiy Proezd, 3, Moscow, 125319, Russia
References
1. Van der Aalst W. M. P. Process mining: discovery, conformance and enhancement of business processes. Springer, 2011.
2. Van der Aalst W.M.P., Weijters A.J.M.M., Maruster L. Workflow Mining: Discovering Process Models from Event Logs // IEEE Transactions on Knowledge and Data Engineering, 2004. Vol. 16(9). P. 1128–1142.
3. Van der Aalst W.M.P., Adriansyah A., Van Dongen B.F. Replaying history on process models for conformance checking and performance analysis // Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery. Vol. 2(2). Wiley Online Library. 2012. P. 182–192.
4. Adriansyah A., Van Dongen B.F., Van der Aalst W.M.P. Conformance checking using costbased fitness analysis // 15th IEEE International Conference on Enterprise Distributed Object Computing Conference (EDOC). 2011. P. 55–64.
5. Adriansyah A., Van Dongen B.F., Van der Aalst W.M.P. Towards robust conformance checking // Business Process Management Workshops. Springer. 2011. P. 122–133.
6. Adriansyah A., Munoz-Gama J., Carmona J., Van Dongen B.F., Van der Aalst W.M.P. Alignment Based Precision Checking // Business Process Management Workshops. Springer. 2012. P. 137–149.
7. Buijs J.C.A.M., Van Dongen B.F., Van der Aalst W.M.P. On the Role of Fitness, Precision, Generalization and Simplicity in Process Discovery // 20th International Conference on Cooperative Information Systems (CoopIS 2012). Ser. lncs. 2012.
8. Van Dongen B. F., Van der Aalst W. M. P., G¨unther C. W., Rozinat A., Verbeek E., Weijters T. ProM: the process mining toolkit // Business Process Management Demonstration Track (BPMDemos2009). Ser. CEUR Workshop Proceedings, A. K. A. d. Medeiros and B. Weber, Eds. 2009. Vol. 489. P. 1–4.
9. Kalenkova A. A., Lomazova I. A. Discovery of Cancellation Regions within Process Mining Techniques // Proceedings of the 22nd International Workshop on Concurrency, Specification and Programming. Warsaw, Poland, 2013. P. 232–244.
10. Kalenkova A. A., Lomazova I. A., Van der Aalst W. M. P. Process Model Discovery: A Method Based on Transition System Decomposition // Application and Theory of Petri Nets and Concurrency, LNCS 8489. Springer, 2014. P. 71–90.
11. Leemans S. J. J., Fahland D., Van der Aalst W. M. P. Discovering Block-Structured Process Models from Incomplete Event Logs. Tech. Rep. BPM-14-05. Eindhoven University of Technology. March 2014.
12. Munoz-Gama J., Carmona J., Van der Aalst W. M. P. Conformance Checking in the Large: Partitioning and Topology // International Conference on Business Process Management (BPM 2013), LNCS 8094. Springer-Verlag, Berlin, 2013. P. 130–145.
13. Verbeek H. M. W., Buijs J. C. A. M., Van Dongen B. F., Van der Aalst W. M. P. Prom 6: The process mining toolkit // Proceedings of BPM Demonstration Track. 2010. Vol. 615. P. 34—39.
14. Verbeek H. M. W., Buijs J. C. A. M., Van Dongen B. F., Van der Aalst W. M. P. XES, XESame, and ProM 6 // Information Systems Evolution, Lecture Notes in Business Information Processing. 2011. Vol. 72. P. 60–75. DOI : 10.1007/978-3-642-17722-4_5
15. http://www.xes-standard.org/xesstandarddefinition
16. Rogge-Solti A., Mans R. S., Van der Aalst W. M. P., Weske M. Repairing Event Logs Using Timed Process Models // OTM 2013 Workshops, LNCS 8186. 2013. P. 705–708.
17. Rozinat A. Process Mining: Conformance and Extension. PhD Thesis, Eindhoven University of Technology. 2010.
18. Rubin V. A., Lomazova I. A., Van der Aalst W. M. P. Agile Development with Software Process Mining // Proceedings of the 2014 International Conference on Software and System Process (ICSSP 2014). Nanjing, China. ACM, 2014. P. 70–74.
19. Rubin V. A., Mitsyuk A. A., Lomazova I. A., Van der Aalst W. M. P. Process Mining Can Be Applied to Software Too! // Proceedings of the 8th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM 2014). Torino, Italy. ACM, 2014. P. 57:1–57:8.
20. Shugurov I., Mitsyuk A. A. Generation of a Set of Event Logs with Noise // Proceedings of the 8th Spring/Summer Young Researchers’ Colloquium on Software Engineering (SYRCoSE 2014). 2014. P. 88–95.
21. http://pais.hse.ru/research/projects/gena
22. Van der Werf J. M. E. M. et al. Process discovery using integer linear programming // Applications and Theory of Petri Nets. Springer Berlin Heidelberg, 2008. P. 368–387.
23. Weijters A., Van der Aalst W. M. P., De Medeiros A. K. A. Process mining with the heuristics miner-algorithm // Technische Universiteit Eindhoven, Tech. Rep. WP. 2006. Vol. 166. P. 1–34.
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For citations:
Mitsyuk A.A., Shugurov I.S. On Process Model Synthesis Based on Event Logs with Noise. Modeling and Analysis of Information Systems. 2014;21(4):181-198. (In Russ.) https://doi.org/10.18255/1818-1015-2014-4-181-198
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