Process Mining: Realization and Optimization of Process Discovery Algorithm

Abstract

The article discusses the approach to the analysis of business processes, called process mining, and the directions of its application. In particular, a description of the process discovery algorithm is provided, with the help of which the process model is reconstructed from the event log in the form of a workflow graph. The implementation and improvement of the algorithm are proposed, which allow avoiding costly enumeration of all subsets of activities included in the analyzed process model. The proposed approach allows the use of process discovery algorithm for large event logs.

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REFERENCES

  1. 1

    W. M. van der Aalst, Process Mining. Discovery, Conformance and Enhancement of Business Processes (Springer, New York, 2011).

    Google Scholar 

  2. 2

    J. Jeston and J. Nelis, Business Process Management. Practical Guidelines to Successful Implementations (Routledge, London, New York, 2014).

    Google Scholar 

  3. 3

    K. van Hee, Workflow Management: Models, Methods, and Systems (Information Systems) (MIT Press, Boston, 2004).

    Google Scholar 

  4. 4

    M. Dumas, W. M. van der Aalst, and A. H. ter Hofstede, Process Aware Information Systems: Bridging People and Software Through Process Technology (Wiley-Interscience, New York, 2005).

    Google Scholar 

  5. 5

    S. L. Mansar and H. A. Reijers, ‘‘Best practices in business process redesign: Validation of a redesign framework,’’ Comput. Ind. 56, 457–471 (2005).

    Article  Google Scholar 

  6. 6

    M. Dumas, M. La Rosa, J. Mendling, and H. A. Reijers, Fundamentals of Business Process Management (Springer, New York, 2018).

    Google Scholar 

  7. 7

    A. Rozinat and W. M. van der Aalst, ‘‘Conformance checking of process based on monitoring real behavior,’’ Inform. Syst. 33, 64–95 (2008).

    Article  Google Scholar 

  8. 8

    A. Burattin, A. Sperduti, and M. Veluscek, ‘‘Business models enhancement through discovery of roles,’’ in Proceedings of the IEEE Symposium on Computational Intelligence and Data Mining (2013), pp. 103–110.

  9. 9

    J. Mendling, Business Process Management. Metrics for Process Models (Springer, Cham, 2008), pp. 1–15.

    Google Scholar 

  10. 10

    R. Agrawal, D. Gunopulos, and F. Leymann, ‘‘Mining process models from workflow logs,’’ in Proceedings of the 6th International Conference on Extended Database Technology (1998), pp. 469–483.

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Funding

The work has been done at the JSCC RAS as part of the state assignment for the topic 0065-2019-0016 (reg. no. AAAA-A19-119011590098-8). The supercomputer MVS-10P, located at the JSCC RAS, was used for calculations during the research.

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Correspondence to G. I. Savin or A. D. Chopornyak or A. A. Rybakov or S. S. Shumilin.

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(Submitted by A. M. Elizarov)

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Savin, G.I., Chopornyak, A.D., Rybakov, A.A. et al. Process Mining: Realization and Optimization of Process Discovery Algorithm. Lobachevskii J Math 41, 2566–2574 (2020). https://doi.org/10.1134/S199508022012032X

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Keywords:

  • process mining
  • process discovery algorithm
  • Petri nets
  • process model
  • event logs