Probabilistic Optimization of Semantic Process Model Matching

H. Leopold, M. Niepert, M. Weidlich, J. Mendling, R.M. Dijkman, H. Stuckenschmidt

Research output: Chapter in Book/Report/Conference proceedingChapterAcademic

63 Citations (Scopus)


Business process models are increasingly used by companies, often yielding repositories of several thousand models. These models are of great value for business analysis such as service identification or process standardization. A problem is though that many of these analyses require the pairwise comparison of process models, which is hardly feasible to do manually given an extensive number of models. While the computation of similarity between a pair of process models has been intensively studied in recent years, there is a notable gap on automatically matching activities of two process models. In this paper, we develop an approach based on semantic techniques and probabilistic optimization. We evaluate our approach using a sample of admission processes from different universities.
Original languageEnglish
Title of host publicationBusiness process management : proceedings of the 10th international conference on business process management (BPM)
EditorsA. Barros, A. Gal, E. Kindler
Place of PublicationTallinn, Estonia
ISBN (Print)978-3-642-32884-8
Publication statusPublished - 2012
Event10th International Conference on Business Process Management (BPM 2012) - Tallinn, Estonia
Duration: 3 Sep 20126 Sep 2012
Conference number: 10

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743


Conference10th International Conference on Business Process Management (BPM 2012)
Abbreviated titleBPM 2012


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