Abstract
Massive event logs are produced in information systems, which record executions of business processes in organizations. Various techniques are proposed to discover process models reflecting real-life behaviors from these logs. However, the discovered models are mostly in Petri nets rather than BPMN models, the current industrial process modeling standard. Conforti et al. and Weber et al. propose techniques that discover BPMN models with sub-processes, multi-instance, etc. However, these techniques are made for event logs with special attributes, e.g., containing attributes about primary and foreign keys, which may not commonly appear in event logs. For example, logs from the OA (office automation) systems of CMCC (China Mobile Communications Corporation) do not contain such data. To solve this issue, this paper proposes two techniques that can discover BPMN models with sub-processes and multi-instance markers with event logs containing less event attributes. One of our techniques only requires four event attributes: case id, task name, start time and end time. Experimental evaluations with both real-life logs and synthetic logs show that our techniques can indeed discover process models with sub-process and multi-instance markers from logs with less event attributes, and are more accurate and less complex than those derived with flat process model discovery techniques.
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References
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)
de Medeiros, A.K.A., van Dongen, B.F., van der Aalst, W.M.P., Weijters, A.J.M.M.: Process mining for ubiquitous mobile systems: an overview and a concrete algorithm. In: Baresi, L., Dustdar, S., Gall, H.C., Matera, M. (eds.) UMICS 2004. LNCS, vol. 3272, pp. 151–165. Springer, Heidelberg (2004)
Wen, L., Wang, J., van der Aalst, W.M.P., et al.: A novel approach for process mining based onevent types. Journal of Intelligent Information Systems 32(2), 163–190 (2009)
Wen, L., van der Aalst, W.M.P., Wang, J., et al.: Mining process models with non-free-choice constructs. Data Mining and Knowledge Discovery 15(2), 145–180 (2007)
Wen, L., Wang, J., Sun, J.: Mining invisible tasks from event logs. In: Dong, G., Lin, X., Wang, W., Yang, Y., Yu, J.X. (eds.) APWeb/WAIM 2007. LNCS, vol. 4505, pp. 358–365. Springer, Heidelberg (2007)
Li, J., Liu, D., Yang, B.: Process mining: extending α-algorithm to mine duplicate tasks in process logs. In: Chang, K.C.-C., Wang, W., Chen, L., Ellis, C.A., Hsu, C.-H., Tsoi, A.C., Wang, H. (eds.) APWeb/WAIM 2007. LNCS, vol. 4537, pp. 396–407. Springer, Heidelberg (2007)
Weijters, A.J.M.M., van der Aalst, W.M.P., de Medeiros, A.K.A.: Process mining with the heuristics miner-algorithm. Technische Universiteit Eindhoven, Tech. Rep. WP 166, 1–34 (2006)
Buijs, J.C.A.M., van Dongen, B.F., van der Aalst, W.M.P.: A genetic algorithm for discovering process trees. In: 2012 IEEE Evolutionary Computation, pp. 1–8 (2012)
Kindler, E., Rubin, V., Schäfer, W.: Process mining and petri net synthesis. In: Eder, J., Dustdar, S. (eds.) BPM Workshops 2006. LNCS, vol. 4103, pp. 105–116. Springer, Heidelberg (2006)
Pesic, M., Schonenberg, H., van der Aalst, W.M.P.: Declare: Full support for loosely-structured processes. In: 11th IEEE International Enterprise Distributed Object Computing Conference, EDOC 2007, pp. 287–287. IEEE (2007)
Pesic, M., van der Aalst, W.M.P.: A declarative approach for flexible business processes management. In: Eder, J., Dustdar, S. (eds.) BPM Workshops 2006. LNCS, vol. 4103, pp. 169–180. Springer, Heidelberg (2006)
De Weerdt, J., vanden Broucke, S.K.L.M., Caron, F.: Bidimensional process discovery for mining BPMN models. In: Fournier, F., Mendling, J. (eds.) BPM 2014 Workshops. LNBIP, vol. 202, pp. 529–540. Springer, Heidelberg (2015)
Li, J., Bose, R.P.J.C., van der Aalst, W.M.P.: Mining context-dependent and interactive business process maps using execution patterns. In: Muehlen, Mz, Su, J. (eds.) BPM 2010 Workshops. LNBIP, vol. 66, pp. 109–121. Springer, Heidelberg (2011)
Conforti, R., Dumas, M., GarcÃa-Bañuelos, L., La Rosa, M.: Beyond tasks and gateways: discovering bpmn models with subprocesses, boundary events and activity markers. In: Sadiq, S., Soffer, P., Völzer, H. (eds.) BPM 2014. LNCS, vol. 8659, pp. 101–117. Springer, Heidelberg (2014)
Ekanayake, C.C., Dumas, M., GarcÃa-Bañuelos, L., La Rosa, M.: Slice, mine and dice: complexity-aware automated discovery of business process models. In: Daniel, F., Wang, J., Weber, B. (eds.) BPM 2013. LNCS, vol. 8094, pp. 49–64. Springer, Heidelberg (2013)
De Weerdt, J., De Backer, M., Vanthienen, J., et al.: A multi-dimensional quality assessment of state-of-the-art process discovery algorithms using real-life event logs. Information Systems 37(7), 654–676 (2012)
Rozinat, A., van der Aalst, W.M.P.: Conformance testing: measuring the fit and appropriateness of event logs and process models. In: Bussler, C.J., Haller, A. (eds.) BPM 2005. LNCS, vol. 3812, pp. 163–176. Springer, Heidelberg (2006)
Weber, I., Farshchi, M., Mendling, J., Schneider, J.G.: Mining processes with multi-instantiation. In: ACM/SIGAPP Symposium on Applied Computing (ACM SAC), Salamanca, Spain, April 2015
Kalenkova, A.A., van der Aalst, W.M.P., Lomazova, I.A., et al.: Process Mining Using BPMN: Relating Event Logs and Process Models. Software and Systems Modeling, 1–25 (2015)
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Wang, Y., Wen, L., Yan, Z., Sun, B., Wang, J. (2015). Discovering BPMN Models with Sub-processes and Multi-instance Markers. In: Debruyne, C., et al. On the Move to Meaningful Internet Systems: OTM 2015 Conferences. OTM 2015. Lecture Notes in Computer Science(), vol 9415. Springer, Cham. https://doi.org/10.1007/978-3-319-26148-5_11
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DOI: https://doi.org/10.1007/978-3-319-26148-5_11
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