Discovering Reference Models by Mining Process Variants Using a Heuristic Approach

Chen Li, Manfred Reichert, Andreas Wombacher

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

65 Citations (Scopus)
126 Downloads (Pure)


Recently, a new generation of adaptive Process-Aware Information Systems (PAISs) has emerged, which enables structural process changes during runtime. Such flexibility, in turn, leads to a large number of process variants derived from the same model, but differing in structure. Generally, such variants are expensive to configure and maintain. This paper provides a heuristic search algorithm which fosters learning from past process changes by mining process variants. The algorithm discovers a reference model based on which the need for future process configuration and adaptation can be reduced. It additionally provides the flexibility to control the process evolution procedure, i.e., we can control to what degree the discovered reference model differs from the original one. As benefit, we cannot only control the effort for updating the reference model, but also gain the flexibility to perform only the most important adaptations of the current reference model. Our mining algorithm is implemented and evaluated by a simulation using more than 7000 process models. Simulation results indicate strong performance and scalability of our algorithm even when facing large-sized process models.
Original languageEnglish
Title of host publicationBusiness Process Management
Subtitle of host publication7th International Conference, BPM 2009, Ulm, Germany, September 8-10, 2009. Proceedings
EditorsUmeshwar Dayal, Johann Eder, Jana Koehler, Hajo A. Reijers
Place of PublicationLondon
Number of pages18
ISBN (Print)978-3-642-03847-1
Publication statusPublished - Sept 2009
Event7th International Conference on Business Process Management, BPM 2009 - Ulm, Germany
Duration: 8 Sept 200910 Sept 2009
Conference number: 7

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference7th International Conference on Business Process Management, BPM 2009
Abbreviated titleBPM


  • METIS-263996
  • SCS-Services
  • EWI-16004
  • IR-67581


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