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Automatic Root Cause Identification Using Most Probable Alignments

  • Marie Koorneef
  • Andreas Solti
  • Henrik LeopoldEmail author
  • Hajo A. Reijers
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 308)

Abstract

In many organizational contexts, it is important that behavior conforms to the intended behavior as specified by process models. Non-conforming behavior can be detected by aligning process actions in the event log to the process model. A probable alignment indicates the most likely root cause for non-conforming behavior. Unfortunately, available techniques do not always return the most probable alignment and, therefore, also not the most probable root cause. Recognizing this limitation, this paper introduces a method for computing the most probable alignment. The core idea of our approach is to use the history of an event log to assign probabilities to the occurrences of activities and the transitions between them. A theoretical evaluation demonstrates that our approach improves upon existing work.

Keywords

Conformance checking Root cause analysis Most probable alignments 

Notes

Acknowledgement

We thank Massimiliano de Leoni for validating our understanding of [5].

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Marie Koorneef
    • 1
  • Andreas Solti
    • 2
  • Henrik Leopold
    • 1
    Email author
  • Hajo A. Reijers
    • 1
    • 3
  1. 1.Department of Computer SciencesVrije Universiteit AmsterdamAmsterdamThe Netherlands
  2. 2.Institute for Information BusinessVienna University of Economics and BusinessViennaAustria
  3. 3.Department of Mathematics and Computer ScienceEindhoven University of TechnologyEindhovenThe Netherlands

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