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Towards Confirmatory Process Discovery: Making Assertions About the Underlying System

Author

Listed:
  • Gert Janssenswillen

    (Hasselt University
    Research Foundation Flanders (FWO))

  • Benoît Depaire

    (Hasselt University)

Abstract

The focus in the field of process mining, and process discovery in particular, has thus far been on exploring and describing event data by the means of models. Since the obtained models are often directly based on a sample of event data, the question whether they also apply to the real process typically remains unanswered. As the underlying process is unknown in real life, there is a need for unbiased estimators to assess the system-quality of a discovered model, and subsequently make assertions about the process. In this paper, an experiment is described and discussed to analyze whether existing fitness, precision and generalization metrics can be used as unbiased estimators of system fitness and system precision. The results show that important biases exist, which makes it currently nearly impossible to objectively measure the ability of a model to represent the system.

Suggested Citation

  • Gert Janssenswillen & Benoît Depaire, 2019. "Towards Confirmatory Process Discovery: Making Assertions About the Underlying System," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 61(6), pages 713-728, December.
    • Handle: RePEc:spr:binfse:v:61:y:2019:i:6:d:10.1007_s12599-018-0567-8
    DOI: 10.1007/s12599-018-0567-8
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    References listed on IDEAS

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    1. Anindya Datta, 1998. "Automating the Discovery of AS-IS Business Process Models: Probabilistic and Algorithmic Approaches," Information Systems Research, INFORMS, vol. 9(3), pages 275-301, September.
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