Supporting Rule-Based Process Mining by User-Guided Discovery of Resource-Aware Frequent Patterns

  • Stefan Schönig
  • Florian Gillitzer
  • Michael Zeising
  • Stefan Jablonski
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8954)


Agile processes depend on human resources, decisions and expert knowledge and are especially versatile and comprise rather complex coherencies. Rule-based process models are well-suited for modeling these processes. There exist a number of process mining approaches to discover rule-based process models from event logs. However, existing rule-based approaches are typically based on a given set of rule templates and predominately consider control flow aspects. By only considering a given set of templates, contemporary approaches underlie a representational bias. The usage of a fixed language frequently ends into insuffcient languages. In this paper we propose an approach to automatically suggest adequate resource-aware rule templates for a given domain by pre-processing the provided event log using frequent pattern mining techniques. These templates can then be instantiated and checked by process mining methods.


Rule-based process mining Resource-aware process mining Frequent pattern mining 



The presented work is developed and used in the project “Kompetenzzentrum für praktisches Prozess- und Qualitätsmanagement”, which is funded by “Europäischer Fonds für regionale Entwicklung (EFRE)”.


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Stefan Schönig
    • 1
  • Florian Gillitzer
    • 1
  • Michael Zeising
    • 1
  • Stefan Jablonski
    • 1
  1. 1.University of BayreuthBayreuthGermany

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