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Process Mining and the Black Swan: An Empirical Analysis of the Influence of Unobserved Behavior on the Quality of Mined Process Models

  • Jana-Rebecca RehseEmail author
  • Peter Fettke
  • Peter Loos
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 308)

Abstract

In this paper, we present the epistomological problem of induction, illustrated by the metaphor of the black swan, and its relevance for Process Mining. The quality of mined models is typically measured in terms of four dimensions, namely fitness, precision, simplicity, and generalization. Both precision and generalization rely on the definition of “unobserved behavior”, i.e. traces not contained in the log. This paper is intended to analyze the influence of unobserved behavior, the potential black swan, has on the quality of mined models. We conduct an empirical analysis to investigate the relation between a system, its observed and unobserved behavior and the mined models. The results show that the unobserved behavior, mainly determined by the nature of the unknown system, can have a significant impact on the quality assessment of mined models, hence eliciting the need to explicate and discuss the assumptions underlying the notions of unobserved behavior in more depth.

Keywords

Process mining Process discovery Evaluation metrics Process model quality 

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Institute for Information Systems (IWi) at the German Center for Artificial Intelligence (DFKI GmbH), Saarland UniversitySaarbrueckenGermany

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