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Predicting the Quality of Process Model Matching

  • Conference paper
Book cover Business Process Management

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8094))

Abstract

Process model matching refers to the task of creating correspondences among activities of different process models. This task is crucial whenever comparison and alignment of process models are called for. In recent years, there have been a few attempts to tackle process model matching. Yet, evaluating the obtained sets of correspondences reveals high variability in the results. Addressing this issue, we propose a method for predicting the quality of results derived by process model matchers. As such, prediction serves as a case-by-case decision making tool in estimating the amount of trust one should put into automatic matching. This paper proposes a model of prediction for process matching based on both process properties and preliminary match results.

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Author information

Authors and Affiliations

  1. Technion - Israel Institute of Technology, Technion City, 32000, Haifa, Israel

    Matthias Weidlich, Tomer Sagi & Avigdor Gal

  2. Humboldt-Universität zu Berlin, Unter den Linden 6, 10099, Berlin, Germany

    Henrik Leopold

  3. Wirtschaftsuniversität Wien, Augasse 2-6, A-1090, Vienna, Austria

    Jan Mendling

Authors
  1. Matthias Weidlich
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  2. Tomer Sagi
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  3. Henrik Leopold
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  4. Avigdor Gal
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  5. Jan Mendling
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Editor information

Editors and Affiliations

  1. Department of Information Engineering and Computer Science, University of Trento, 38123, Povo, TN, Italy

    Florian Daniel

  2. Institute of Information System and Engineering of School Software, Tsinghua University, 100084, Beijing, China

    Jianmin Wang

  3. Business Process Management Research Cluster, University of Innsbruck, 6020, Innsbruck, Austria

    Barbara Weber

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Weidlich, M., Sagi, T., Leopold, H., Gal, A., Mendling, J. (2013). Predicting the Quality of Process Model Matching. In: Daniel, F., Wang, J., Weber, B. (eds) Business Process Management. Lecture Notes in Computer Science, vol 8094. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40176-3_16

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  • DOI: https://doi.org/10.1007/978-3-642-40176-3_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-40175-6

  • Online ISBN: 978-3-642-40176-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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