Listen to me: Improving process model matching through user feedback

Christopher Klinkmüller, Henrik Leopold, Ingo Weber, Jan Mendling, André Ludwig

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

25 Scopus citations


Many use cases in business process management rely on the identification of correspondences between process models. However, the sparse information in process models makes matching a fundamentally hard problem. Consequently, existing approaches yield a matching quality which is too low to be useful in practice. Therefore, we investigate incorporating user feedback to improve matching quality. To this end, we examine which information is suitable for feedback analysis. On this basis, we design an approach that performs matching in an iterative, mixed-initiative approach: we determine correspondences between two models automatically, let the user correct them, and analyze this input to adapt the matching algorithm. Then, we continue with matching the next two models, and so forth. This approach improves the matching quality, as showcased by a comparative evaluation. From this study, we also derive strategies on how to maximize the quality while limiting the additional effort required from the user.

Original languageEnglish
Title of host publicationBusiness Process Management - 12th International Conference, BPM 2014, Proceedings
PublisherSpringer Verlag
Number of pages17
ISBN (Print)9783319101712
StatePublished - 2014
Externally publishedYes
Event12th International Conference on Business Process Management, BPM 2014 - Haifa, Israel
Duration: 7 Sep 201411 Sep 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8659 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference12th International Conference on Business Process Management, BPM 2014


  • BPM
  • process model matching
  • process similarity


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