Simplifying Mined Process Models: An Approach Based on Unfoldings

  • Dirk Fahland
  • Wil M. P. van der Aalst
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6896)


Process models discovered using process mining tend to be complex and have problems balancing between overfitting and underfitting. Overfitting models are not general enough while underfitting models allow for too much behavior. This paper presents a post-processing approach to simplify discovered process models while controlling the balance between overfitting and underfitting. The discovered process model, expressed in terms of a Petri net, is unfolded into a branching process using the event log. Subsequently, the resulting branching process is folded into a simpler process model capturing the desired behavior.


process mining model simplification Petri nets branching processes 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    van der Aalst, W.: Process Mining: Discovery, Conformance and Enhancement of Business Processes. Springer, Heidelberg (2011)CrossRefzbMATHGoogle Scholar
  2. 2.
    van Dongen, B., de Medeiros, A.A., Wen, L.: Process Mining: Overview and Outlook of Petri Net Discovery Algorithms. ToPNOC 2, 225–242 (2009)Google Scholar
  3. 3.
    Weijters, A., van der Aalst, W.: Rediscovering Workflow Models from Event-Based Data using Little Thumb. Integrated Computer-Aided Engineering 10(2), 151–162 (2003)Google Scholar
  4. 4.
    Günther, C., van der Aalst, W.: Fuzzy Mining: Adaptive Process Simplification Based on Multi-perspective Metrics. In: Alonso, G., Dadam, P., Rosemann, M. (eds.) BPM 2007. LNCS, vol. 4714, pp. 328–343. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  5. 5.
    Medeiros, A., Weijters, A., van der Aalst, W.: Genetic Process Mining: An Experimental Evaluation. Data Mining and Knowledge Discovery 14(2), 245–304 (2007)CrossRefGoogle Scholar
  6. 6.
    van Dongen, B., van der Aalst, W.: Multi-Phase Process Mining: Building Instance Graphs. In: Atzeni, P., Chu, W., Lu, H., Zhou, S., Ling, T.-W. (eds.) ER 2004. LNCS, vol. 3288, pp. 362–376. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  7. 7.
    Carmona, J., Cortadella, J.: Process Mining Meets Abstract Interpretation. In: Balcázar, J.L., Bonchi, F., Gionis, A., Sebag, M. (eds.) ECML PKDD 2010. LNCS, vol. 6321, pp. 184–199. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  8. 8.
    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)CrossRefGoogle Scholar
  9. 9.
    van der Werf, J., van Dongen, B., Hurkens, C., Serebrenik, A.: Process Discovery using Integer Linear Programming. Fundamenta Informaticae 94, 387–412 (2010)zbMATHGoogle Scholar
  10. 10.
    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. Software and System Modeling 9(1), 87–111 (2010)CrossRefGoogle Scholar
  11. 11.
    Adriansyah, A., van Dongen, B., van der Aalst, W.: Towards Robust Conformance Checking. In: Muehlen, M., Su, J. (eds.) TEMPO. LNBIP, vol. 66, pp. 122–133. Springer, Heidelberg (2011)Google Scholar
  12. 12.
    Esparza, J., Römer, S., Vogler, W.: An Improvement of McMillan’s Unfolding Algorithm. Formal Methods in System Design 20(3), 285–310 (2002)CrossRefzbMATHGoogle Scholar
  13. 13.
    Engelfriet, J.: Branching Processes of Petri Nets. Acta Informatica 28(6), 575–591 (1991)CrossRefzbMATHGoogle Scholar
  14. 14.
    Colom, J., Silva, M.: Improving the Linearly Based Characterization of P/T Nets. In: Rozenberg, G. (ed.) APN 1990. LNCS, vol. 483, pp. 113–145. Springer, Heidelberg (1991)CrossRefGoogle Scholar
  15. 15.
    Rozinat, A., van der Aalst, W.: Conformance Checking of Processes Based on Monitoring Real Behavior. Information Systems 33(1), 64–95 (2008)CrossRefGoogle Scholar
  16. 16.
    Muñoz-Gama, J., Carmona, J.: A Fresh Look at Precision in Process Conformance. In: Hull, R., Mendling, J., Tai, S. (eds.) BPM 2010. LNCS, vol. 6336, pp. 211–226. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  17. 17.
    Polyvyanyy, A., García-Bañuelos, L., Dumas, M.: Structuring Acyclic Process Models. In: Hull, R., Mendling, J., Tai, S. (eds.) BPM 2010. LNCS, vol. 6336, pp. 276–293. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  18. 18.
    Vanhatalo, J., Völzer, H., Koehler, J.: The Refined Process Structure Tree. Data Knowledge Engineering 68(9), 793–818 (2009)CrossRefGoogle Scholar
  19. 19.
    Lüder, A., Hanisch, H.: Synthesis of Admissible Behavior of Petri Nets for Partial Order Specifications. In: WODES 2000, pp. 409–431. Kluwer, Dordrecht (2000)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Dirk Fahland
    • 1
  • Wil M. P. van der Aalst
    • 1
  1. 1.Eindhoven University of TechnologyThe Netherlands

Personalised recommendations