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Business & Information Systems Engineering

, Volume 61, Issue 6, pp 713–728 | Cite as

Towards Confirmatory Process Discovery: Making Assertions About the Underlying System

  • Gert JanssenswillenEmail author
  • Benoît Depaire
Research Paper
First Online:

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.

Keywords

Process mining Process discovery Process quality Fitness Precision Generalization Exploratory data analysis Confirmatory data analysis 
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Notes

Acknowledgements

The computational resources and services used in this work for both process discovery and process conformance tasks were provided by the VSC (Flemish Supercomputer Center), funded by the Research Foundation - Flanders (FWO) and the Flemish Government.

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Copyright information

© Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature 2018

Authors and Affiliations

  1. 1.Hasselt UniversityDiepenbeekBelgium
  2. 2.Research Foundation Flanders (FWO)BrusselsBelgium

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