Abstract
This work presents a set of methods to improve the understandability of process models. Traditionally, simplification methods trade off quality metrics, such as fitness or precision. Conversely, the methods proposed in this paper produce simplified models while preserving or even increasing fidelity metrics. The first problem addressed in the paper is the discovery of duplicate tasks. A new method is proposed that avoids overfitting by working on the transition system generated by the log. The method is able to discover duplicate tasks even in the presence of concurrency and choice. The second problem is the structural simplification of the model by identifying optional and repetitive tasks. The tasks are substituted by annotated events that allow the removal of silent tasks and reduce the complexity of the model. An important feature of the methods proposed in this paper is that they are independent from the actual miner used for process discovery.
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Notes
- 1.
\(\mathcal {B}(A)\) denotes the set of all multisets over A.
References
van der Aalst, W.M.P.: Process Mining - Discovery: Conformance and Enhancement of Business Processes. Springer, Heidelberg (2011)
van der Aalst, W., Rubin, V., Verbeek, H., van Dongen, B., Kindler, E., Gnther, C.: Process mining: a two-step approach to balance between underfitting and overfitting. Softw. & Syst. Model. 9(1), 87–111 (2010)
de Medeiros, A.K.A.: Genetic process mining. Ph.D. thesis, Technische Universiteit Eindhoven, Eindhoven, The Netherlands (2006)
Carmona, J.: The label splitting problem. In: Jensen, K., van der Aalst, W.M., Ajmone Marsan, M., Franceschinis, G., Kleijn, J., Kristensen, L.M. (eds.) Transactions on Petri Nets and Other Models of Concurrency VI. LNCS, vol. 7400, pp. 1–23. Springer, Heidelberg (2012)
Song, J.L., Luo, T.J., Chen, S., Liu, W.: A clustering based method to solve duplicate tasks problem. J. Univ. Chin. Acad. Sci. 26(1), 107 (2009)
Vázquez-Barreiros, B., Mucientes, M., Lama, M.: Mining duplicate tasks from discovered processes. In: Proceedings of Algorithms and Theories for the Analysis of Event Data, vol. 1371, Brussels, Belgium, CEUR, pp. 78–82 June 2015
Leemans, S.J.J., Fahland, D., van der Aalst, W.M.P.: Discovering block-structured process models from incomplete event logs. In: Ciardo, G., Kindler, E. (eds.) PETRI NETS 2014. LNCS, vol. 8489, pp. 91–110. Springer, Heidelberg (2014)
Murata, T.: Petri nets: properties, analysis and applications. Proc. IEEE 77(4), 541–574 (1989)
Johnson, S.C.: Hierarchical clustering schemes. Psychometrika 32(3), 241–254 (1967)
Jones, E., Oliphant, T., Peterson, P., et al.: SciPy: open source scientific tools for Python (2001) . Accessed 18 Mar 2016
van der Aalst, W.M.P., Dumas, M., Ouyang, C., Rozinat, A., Verbeek, E.: Conformance checking of service behavior. ACM Trans. Internet Technol. 8(3), 1–13 (2008)
van Dongen, B.F., de Medeiros, A.K.A., Verbeek, H.M.W.E., Weijters, A.J.M.M.T., van der Aalst, W.M.P.: The ProM framework: a new era in process mining tool support. In: Ciardo, G., Darondeau, P. (eds.) ICATPN 2005. LNCS, vol. 3536, pp. 444–454. Springer, Heidelberg (2005)
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 Comput. 23(3), 333–363 (2011)
Carmona, J., Sol, M.: PMLAB: an scripting environment for process mining. In: Proceedings of the BPM Demo Sessions 2014, pp. 16–21 (2014)
Carmona, J.A., Cortadella, J., Kishinevsky, M.: A region-based algorithm for discovering petri nets from event logs. In: Dumas, M., Reichert, M., Shan, M.-C. (eds.) BPM 2008. LNCS, vol. 5240, pp. 358–373. Springer, Heidelberg (2008)
Adriansyah, A., Munoz-Gama, J., Carmona, J., van Dongen, B., van der Aalst, W.: Measuring precision of modeled behavior. Inf. Syst. e-Bus. Manag. 13(1), 37–67 (2015)
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. In: Meersman, R., Panetto, H., Dillon, T., Rinderle-Ma, S., Dadam, P., Zhou, X., Pearson, S., Ferscha, A., Bergamaschi, S., Cruz, I.F. (eds.) OTM 2012, Part I. LNCS, vol. 7565, pp. 305–322. Springer, Heidelberg (2012)
Gansner, E.R., Koutsofios, E., North, S.C., Vo, K.: A technique for drawing directed graphs. IEEE Trans. Softw. Eng. 19(3), 214–230 (1993)
Herbst, J., Karagiannis, D.: Workflow mining with InWoLvE. Comput. Ind. 53(3), 245–264 (2004). Process / Workflow Mining
Burattin, A., Sperduti, A.: PLG: a framework for the generation of business process models and their execution logs. In: Muehlen, M., Su, J. (eds.) BPM 2010 Workshops. LNBIP, vol. 66, pp. 214–219. Springer, Heidelberg (2011)
Bose, R.: Process mining in the large: preprocessing, discovery, and diagnostics. Ph.D. thesis, Technische Universiteit Eindhoven (2012)
van den Broucke, S.K.L.M.: Advances in Process Mining. Ph.D., Katholieke Universiteit Leuven (2014)
Goedertier, S., Martens, D., Vanthienen, J., Baesens, B.: Robust process discovery with artificial negative events. J. Mach. Learn. Res. 10, 1305–1340 (2009)
Li, J., Liu, D., Yang, B.: Process mining: extending \(\alpha \)-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)
De San Pedro, J., Carmona, J., Cortadella, J.: Log-based simplification of process models. In: Motahari-Nezhad, H.R., Recker, J., Weidlich, M. (eds.) BPM 2015. LNCS, vol. 9253, pp. 457–474. Springer International Publishing, Heidelberg (2015)
Fahland, D., van der Aalst, W.M.P.: Simplifying discovered process models in a controlled manner. Inf. Syst. 38(4), 585–605 (2013)
Acknowledgments
This work has been partially supported by funds from the Spanish Ministry for Economy and Competitiveness and the European Union (FEDER funds) under grant TIN2013-46181-C2-1-R, and the Generalitat de Catalunya (2014 SGR 1034 and FI-DGR 2015).
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de San Pedro, J., Cortadella, J. (2016). Discovering Duplicate Tasks in Transition Systems for the Simplification of Process Models. In: La Rosa, M., Loos, P., Pastor, O. (eds) Business Process Management. BPM 2016. Lecture Notes in Computer Science(), vol 9850. Springer, Cham. https://doi.org/10.1007/978-3-319-45348-4_7
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