Abstract
In process discovery, the goal is to find, for a given event log, the model describing the underlying process. While process models can be represented in a variety of ways, in this paper we focus on the representation by Petri nets. Using an approach inspired by language-based regions, we start with a Petri net without any places, and then insert the maximal set of places considered fitting with respect to the behavior described by the log. Traversing and evaluating the whole set of all possible places is not feasible since their number is exponential in the number of activities. Therefore, we propose a strategy to drastically prune this search space to a small number of candidates, while still ensuring that all fitting places are found. This allows us to derive complex model structures that other discovery algorithms fail to discover. In contrast to traditional region-based approaches this new technique can handle infrequent behavior and therefore also noisy real-life event data. The drastic decrease of computation time achieved by our pruning strategy, as well as our noise handling capability, is demonstrated and evaluated by performing various experiments.
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References
van der Aalst, W.: Process Mining: Data Science in Action, 2nd edn. Springer, Heidelberg (2016). https://doi.org/10.1007/978-3-662-49851-4
Bergenthum, R., Desel, J., Lorenz, R., Mauser, S.: Process mining based on regions of languages. In: Alonso, G., Dadam, P., Rosemann, M. (eds.) BPM 2007. LNCS, vol. 4714, pp. 375–383. Springer, Heidelberg (2007). https://doi.org/10.1007/978-3-540-75183-0_27
van der Aalst, W.: Discovering the “glue” connecting activities - exploiting monotonicity to learn places faster. In: It’s All About Coordination - Essays to Celebrate the Lifelong Scientific Achievements of Farhad Arbab, pp. 1–20 (2018)
Wen, L., van der Aalst, W., Wang, J., Sun, J.: Mining process models with non-free-choice constructs. Data Min. Knowl. Discov. 15(2), 145–180 (2007)
Leemans, S.J.J., Fahland, D., van der Aalst, W.M.P.: Discovering block-structured process models from event logs - a constructive approach. In: Colom, J.-M., Desel, J. (eds.) PETRI NETS 2013. LNCS, vol. 7927, pp. 311–329. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-38697-8_17
Weijters, A., van der Aalst, W.: Rediscovering workflow models from event-based data using little thumb. Integr. Comput.-Aided Eng. 10(2), 151–162 (2003)
Badouel, E., Bernardinello, L., Darondeau, P.: Petri Net Synthesis. TTCSAES. Springer, Heidelberg (2015). https://doi.org/10.1007/978-3-662-47967-4
Ehrenfeucht, A., Rozenberg, G.: Partial (set) 2-structures. Acta Informatica 27(4), 343–368 (1990)
Carmona, J., 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). https://doi.org/10.1007/978-3-540-85758-7_26
van der Aalst, W., Rubin, V., Verbeek, H., van Dongen, B., Kindler, E., Günther, C.W.: Process mining: a two-step approach to balance between underfitting and overfitting. Softw. Syst. Model. 9(1), 87 (2008)
Lorenz, R., Mauser, S., Juhás, G.: How to synthesize nets from languages: A survey. In: Proceedings of the 39th Conference on Winter Simulation: 40 Years! The Best is Yet to Come, WSC 2007, pp. 637–647. IEEE Press, Piscataway (2007)
Darondeau, P.: Deriving unbounded Petri nets from formal languages. In: Sangiorgi, D., de Simone, R. (eds.) CONCUR 1998. LNCS, vol. 1466, pp. 533–548. Springer, Heidelberg (1998). https://doi.org/10.1007/BFb0055646
Bergenthum, R., Desel, J., Lorenz, R., Mauser, S.: Synthesis of Petri nets from finite partial languages. Fundam. Inf. 88(4), 437–468 (2008)
van der Werf, J.M.E.M., van Dongen, B.F., Hurkens, C.A.J., Serebrenik, A.: Process discovery using integer linear programming. In: van Hee, K.M., Valk, R. (eds.) PETRI NETS 2008. LNCS, vol. 5062, pp. 368–387. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-68746-7_24
van Zelst, S.J., van Dongen, B.F., van der Aalst, W.M.P.: Avoiding over-fitting in ILP-based process discovery. In: Motahari-Nezhad, H.R., Recker, J., Weidlich, M. (eds.) BPM 2015. LNCS, vol. 9253, pp. 163–171. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-23063-4_10
van Zelst, S., van Dongen, B., van der Aalst, W.: ILP-based process discovery using hybrid regions. In: ATAED@Petri Nets/ACSD (2015)
Berthelot, G.: Checking properties of nets using transformation. In: Rozenberg, G. (ed.) APN 1985. LNCS, vol. 222, pp. 19–40. Springer, Berlin (1986). https://doi.org/10.1007/BFb0016204
Berthelot, G.: Transformations and decompositions of nets. In: Brauer, W., Reisig, W., Rozenberg, G. (eds.) ACPN 1986. LNCS, vol. 254, pp. 359–376. Springer, Heidelberg (1987). https://doi.org/10.1007/978-3-540-47919-2_13
Colom, J.M., Silva, M.: Improving the linearly based characterization of P/T nets. In: Rozenberg, G. (ed.) ICATPN 1989. LNCS, vol. 483, pp. 113–145. Springer, Heidelberg (1991). https://doi.org/10.1007/3-540-53863-1_23
Garcia-Valles, F., Colom, J.: Implicit places in net systems. In: Proceedings 8th International Workshop on Petri Nets and Performance Models, pp. 104–113 (1999)
Berthomieu, B., Botlan, D.L., Dal-Zilio, S.: Petri net reductions for counting markings. CoRR abs/1807.02973 (2018)
van Dongen, B.F., de Medeiros, A.K.A., Verbeek, H.M.W., Weijters, A.J.M.M., 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). https://doi.org/10.1007/11494744_25
Polato, M.: Dataset belonging to the help desk log of an Italian company (2017)
Mannhardt, F.: Sepsis cases - event log (2016)
De Leoni, M., Mannhardt, F.: Road traffic fine management process (2015)
van der Aalst, W.M.P.: Event Logs and Models Used in Process Mining: Data Science in Action (2016). http://www.processmining.org/event_logs_and_models_used_in_book
Lu, X., Fahland, D., van den Biggelaar, F.J.H.M., van der Aalst, W.M.P.: Handling duplicated tasks in process discovery by refining event labels. In: La Rosa, M., Loos, P., Pastor, O. (eds.) BPM 2016. LNCS, vol. 9850, pp. 90–107. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-45348-4_6
Li, J., Liu, D., Yang, B.: Process mining: extending \({\alpha }\)-algorithm to mine duplicate tasks in process logs. In: Chang, K.C.-C., et al. (eds.) APWeb/WAIM -2007. LNCS, vol. 4537, pp. 396–407. Springer, Heidelberg (2007). https://doi.org/10.1007/978-3-540-72909-9_43
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). https://doi.org/10.1007/978-3-540-72524-4_38
Acknowledgments
We thank the Alexander von Humboldt (AvH) Stiftung for supporting our research. We thank Alessandro Berti for his support with implementing the eST-Miner, and Sebastiaan J. van Zelst for reviewing this paper.
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Mannel, L.L., van der Aalst, W.M.P. (2019). Finding Complex Process-Structures by Exploiting the Token-Game. In: Donatelli, S., Haar, S. (eds) Application and Theory of Petri Nets and Concurrency. PETRI NETS 2019. Lecture Notes in Computer Science(), vol 11522. Springer, Cham. https://doi.org/10.1007/978-3-030-21571-2_15
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