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International Conference on Business Process Management

BPM 2012: Business Process Management Workshops pp 489–500Cite as

A Runtime Analysis of Graph-Theoretical Algorithms to Detect Patterns in Process Model Collections

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Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 132))

Abstract

Pattern detection serves different purposes in managing large collections of process models, ranging from syntax checking to compliance validation. This paper presents a runtime analysis of four graph-theoretical algorithms for (frequent) pattern detection. We apply these algorithms to large collections of process and data models to demonstrate that, despite their theoretical intractability, they are able to return results within (milli-) seconds. We discuss the relative performance of these algorithms and their applicability in practice.

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Author information

Authors and Affiliations

  1. WWU Muenster - ERCIS, Leonardo-Campus 3, 48149, Muenster, Germany

    Jörg Becker, Dominic Breuker, Patrick Delfmann, Hanns-Alexander Dietrich & Matthias Steinhorst

Authors
  1. Jörg Becker
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  2. Dominic Breuker
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  3. Patrick Delfmann
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  4. Hanns-Alexander Dietrich
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  5. Matthias Steinhorst
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Editor information

Editors and Affiliations

  1. Queensland University of Technology, Brisbane, QLD, Australia

    Marcello La Rosa

  2. University of Haifa, Haifa, Israel

    Pnina Soffer

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Becker, J., Breuker, D., Delfmann, P., Dietrich, HA., Steinhorst, M. (2013). A Runtime Analysis of Graph-Theoretical Algorithms to Detect Patterns in Process Model Collections. In: La Rosa, M., Soffer, P. (eds) Business Process Management Workshops. BPM 2012. Lecture Notes in Business Information Processing, vol 132. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36285-9_50

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  • DOI: https://doi.org/10.1007/978-3-642-36285-9_50

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-36284-2

  • Online ISBN: 978-3-642-36285-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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