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

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Service-Oriented Computing - ICSOC 2014 Workshops

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 8954))

Abstract

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.

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Notes

  1. 1.

    Process Workbench is a process management system that consists of a modeling, execution as well as a mining module. See workbench.kppq.de for more information.

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Acknowledgement

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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Authors and Affiliations

  1. University of Bayreuth, Bayreuth, Germany

    Stefan Schönig, Florian Gillitzer, Michael Zeising & Stefan Jablonski

Authors
  1. Stefan Schönig
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  2. Florian Gillitzer
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  3. Michael Zeising
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  4. Stefan Jablonski
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Corresponding author

Correspondence to Stefan Schönig .

Editor information

Editors and Affiliations

  1. Blaise Pascal University, Aubiere, France

    Farouk Toumani

  2. Politecnico di Milano, Milano, Italy

    Barbara Pernici

  3. Université Paris Dauphine, Paris, France

    Daniela Grigori

  4. Université Claude Bernard Lyon 1, Villeurbanne, France

    Djamal Benslimane

  5. Vienna University of Economics, Vienna, Austria

    Jan Mendling

  6. National Engineering School of Tunis, Tunis, Tunisia

    Nejib Ben Hadj-Alouane

  7. University of Miami, Coral Gables, Florida, USA

    Brian Blake

  8. University Lorraine, Nancy, France

    Olivier Perrin

  9. University of Miami, Coral Gables, Florida, USA

    Iman Saleh Moustafa

  10. Telecom SudParis, Evry, France

    Sami Bhiri

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Schönig, S., Gillitzer, F., Zeising, M., Jablonski, S. (2015). Supporting Rule-Based Process Mining by User-Guided Discovery of Resource-Aware Frequent Patterns. In: Toumani, F., et al. Service-Oriented Computing - ICSOC 2014 Workshops. Lecture Notes in Computer Science(), vol 8954. Springer, Cham. https://doi.org/10.1007/978-3-319-22885-3_10

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  • DOI: https://doi.org/10.1007/978-3-319-22885-3_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-22884-6

  • Online ISBN: 978-3-319-22885-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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