Similarity of business process models: Metrics and evaluation

  • Authors:

  • Remco Dijkman;Marlon Dumas;Boudewijn van Dongen;Reina Käärik;Jan Mendling

  • Affiliations:

  • School of Industrial Engineering, Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven, The Netherlands;Institute of Computer Science, University of Tartu, J Liivi 2, 50409 Tartu, Estonia;Department of Mathematics and Computer Science, Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven, The Netherlands;Institute of Computer Science, University of Tartu, J Liivi 2, 50409 Tartu, Estonia;Institute of Information Systems, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany

  • Venue:
  • Information Systems
  • Year:
  • 2011

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Abstract

It is common for large organizations to maintain repositories of business process models in order to document and to continuously improve their operations. Given such a repository, this paper deals with the problem of retrieving those models in the repository that most closely resemble a given process model or fragment thereof. Up to now, there is a notable research gap on comparing different approaches to this problem and on evaluating them in the same setting. Therefore, this paper presents three similarity metrics that can be used to answer queries on process repositories: (i) node matching similarity that compares the labels and attributes attached to process model elements; (ii) structural similarity that compares element labels as well as the topology of process models; and (iii) behavioral similarity that compares element labels as well as causal relations captured in the process model. These metrics are experimentally evaluated in terms of precision and recall. The results show that all three metrics yield comparable results, with structural similarity slightly outperforming the other two metrics. Also, all three metrics outperform text-based search engines when it comes to searching through a repository for similar business process models.