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Process mining: a two-step approach to balance between underfitting and overfitting

  • W. M. P. van der Aalst
  • V. Rubin
  • H. M. W. Verbeek
  • B. F. van Dongen
  • E. Kindler
  • C. W. Günther
Open Access
Regular Paper

Abstract

Process mining includes the automated discovery of processes from event logs. Based on observed events (e.g., activities being executed or messages being exchanged) a process model is constructed. One of the essential problems in process mining is that one cannot assume to have seen all possible behavior. At best, one has seen a representative subset. Therefore, classical synthesis techniques are not suitable as they aim at finding a model that is able to exactly reproduce the log. Existing process mining techniques try to avoid such “overfitting” by generalizing the model to allow for more behavior. This generalization is often driven by the representation language and very crude assumptions about completeness. As a result, parts of the model are “overfitting” (allow only for what has actually been observed) while other parts may be “underfitting” (allow for much more behavior without strong support for it). None of the existing techniques enables the user to control the balance between “overfitting” and “underfitting”. To address this, we propose a two-step approach. First, using a configurable approach, a transition system is constructed. Then, using the “theory of regions”, the model is synthesized. The approach has been implemented in the context of ProM and overcomes many of the limitations of traditional approaches.

Keywords

Business Process Transition System Process Mining Customer Relationship Management Region Theory 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

This research is supported by EIT, NWO-EW, and the Technology Foundation STW. Moreover, we would like to thank the many people involved in the development of ProM.

Open Access

This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution,and reproduction in any medium, provided the original author(s) and source are credited.

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Copyright information

© The Author(s) 2008

Authors and Affiliations

  • W. M. P. van der Aalst
    • 1
  • V. Rubin
    • 2
  • H. M. W. Verbeek
    • 1
  • B. F. van Dongen
    • 1
  • E. Kindler
    • 3
  • C. W. Günther
    • 1
  1. 1.Eindhoven University of TechnologyEindhovenThe Netherlands
  2. 2.Software Design and Management (sd&m AG)Offenbach am MainGermany
  3. 3.Technical University of DenmarkInformatics and Mathematical ModellingLyngbyDenmark

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