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How to Make Process Model Matching Work Better? An Analysis of Current Similarity Measures

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Business Information Systems (BIS 2017)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 288))

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Abstract

Process model matching techniques aim at automatically identifying activity correspondences between two process models that represent the same or similar behavior. By doing so, they provide essential input for many advanced process model analysis techniques such as process model search. Despite their importance, the performance of process model matching techniques is not yet convincing and several attempts to improve the performance have not been successful. This raises the question of whether it is really not possible to further improve the performance of process model matching techniques. In this paper, we aim to answer this question by conducting two consecutive analyses. First, we review existing process model matching techniques and give an overview of the specific technologies they use to identify similar activities. Second, we analyze the correspondences of the Process Model Matching Contest 2015 and reflect on the suitability of the identified technologies to identify the missing correspondences. As a result of these analyses, we present a list of three specific recommendations to improve the performance of process model matching techniques in the future.

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Author information

Authors and Affiliations

  1. VU University Amsterdam, De Boelelaan 1081, 1081 HV, Amsterdam, The Netherlands

    Fakhra Jabeen, Henrik Leopold & Hajo A. Reijers

  2. Eindhoven University of Technology, PO Box 513, 5600 MB, Eindhoven, The Netherlands

    Hajo A. Reijers

Authors
  1. Fakhra Jabeen
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  2. Henrik Leopold
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  3. Hajo A. Reijers
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Corresponding author

Correspondence to Henrik Leopold .

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Editors and Affiliations

  1. Poznan University of Economics, Poznan, Poland

    Witold Abramowicz

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Jabeen, F., Leopold, H., Reijers, H.A. (2017). How to Make Process Model Matching Work Better? An Analysis of Current Similarity Measures. In: Abramowicz, W. (eds) Business Information Systems. BIS 2017. Lecture Notes in Business Information Processing, vol 288. Springer, Cham. https://doi.org/10.1007/978-3-319-59336-4_13

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  • DOI: https://doi.org/10.1007/978-3-319-59336-4_13

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  • Online ISBN: 978-3-319-59336-4

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