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Genetic Process Mining: Alignment-Based Process Model Mutation

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Business Process Management Workshops (BPM 2014)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 202))

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Abstract

The Evolutionary Tree Miner (ETM) is a genetic process discovery algorithm that enables the user to guide the discovery process based on preferences with respect to four process model quality dimensions: replay fitness, precision, generalization and simplicity.

Traditionally, the ETM algorithm uses random creation of process models for the initial population, as well as random mutation and crossover techniques for the evolution of generations. In this paper, we present an approach that improves the performance of the ETM algorithm by enabling it to make guided changes to process models, in order to obtain higher quality models in fewer generations. The two parts of this approach are: \((1)\) creating an initial population of process models with a reasonable quality; \((2)\) using information from the alignment between an event log and a process model to identify quality issues in a given part of a model, and resolving those issues using guided mutation operations.

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Notes

  1. 1.

    The event log is publicly available at http://dx.doi.org/10.4121/uuid:a07386a5-7be3- 4367-9535-70bc9e77dbe6.

References

  1. van der Aalst, W.M.P.: Process Mining: Discovery, Conformance and Enhancement of Business Processes. Springer, Heidelberg (2011)

    Book  Google Scholar 

  2. Adriansyah, A., van Dongen, B.F., van der Aalst, W.M.P.: Conformance checking using cost-based fitness analysis. In: 2011 15th IEEE International Enterprise Distributed Object Computing Conference (EDOC), pp. 55–64. IEEE (2011)

    Google Scholar 

  3. 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., et al. (eds.) OTM 2012, Part I. LNCS, vol. 7565, pp. 305–322. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  4. van Eck, M.L.: Alignment-based process model repair and its application to the Evolutionary Tree Miner. Master’s thesis, Technische Universiteit Eindhoven (2013)

    Google Scholar 

  5. Fahland, D., van der Aalst, W.M.P.: Model repair - aligning process models to reality. Inf. Syst. 47, 220–243 (2015)

    Article  Google Scholar 

  6. Gambini, M., La Rosa, M., Migliorini, S., Ter Hofstede, A.H.M.: Automated error correction of business process models. In: Rinderle-Ma, S., Toumani, F., Wolf, K. (eds.) BPM 2011. LNCS, vol. 6896, pp. 148–165. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  7. Küster, J.M., Koehler, J., Ryndina, K.: Improving business process models with reference models in business-driven development. In: Eder, J., Dustdar, S. (eds.) BPM 2006 Workshops. LNCS, vol. 4103, pp. 35–44. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  8. Li, C., Reichert, M., Wombacher, A.: Discovering reference models by mining process variants using a heuristic approach. In: Dayal, U., Eder, J., Koehler, J., Reijers, H.A. (eds.) BPM 2009. LNCS, vol. 5701, pp. 344–362. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  9. Lohmann, N.: Correcting deadlocking service choreographies using a simulation-based graph edit distance. In: Dumas, M., Reichert, M., Shan, M.-C. (eds.) BPM 2008. LNCS, vol. 5240, pp. 132–147. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  10. Verbeek, H.M.W., Buijs, J.C.A.M., van Dongen, B.F., van der Aalst, W.M.P.: XES, XESame, and ProM 6. In: Soffer, P., Proper, E. (eds.) CAiSE Forum 2010. LNBIP, vol. 72, pp. 60–75. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

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Authors and Affiliations

  1. Eindhoven University of Technology, Eindhoven, The Netherlands

    M. L. van Eck, J. C. A. M. Buijs & B. F. van Dongen

Authors
  1. M. L. van Eck
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  2. J. C. A. M. Buijs
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  3. B. F. van Dongen
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Corresponding author

Correspondence to M. L. van Eck .

Editor information

Editors and Affiliations

  1. IBM Research – Haifa, Haifa, Israel

    Fabiana Fournier

  2. Vienna University of Economics and Business, Vienna, Austria

    Jan Mendling

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van Eck, M.L., Buijs, J.C.A.M., van Dongen, B.F. (2015). Genetic Process Mining: Alignment-Based Process Model Mutation. In: Fournier, F., Mendling, J. (eds) Business Process Management Workshops. BPM 2014. Lecture Notes in Business Information Processing, vol 202. Springer, Cham. https://doi.org/10.1007/978-3-319-15895-2_25

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  • DOI: https://doi.org/10.1007/978-3-319-15895-2_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-15894-5

  • Online ISBN: 978-3-319-15895-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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