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State of the Art: Automatic Generation of Business Process Models

Schüler, Selina ORCID iD icon 1; Alpers, Sascha ORCID iD icon 1,2
1 Institut für Angewandte Informatik und Formale Beschreibungsverfahren (AIFB), Karlsruher Institut für Technologie (KIT)
2 FZI Forschungszentrum Informatik (FZI)

Abstract:

Manual Business Process Modeling can be a time-consuming and error-prone process, resulting in low-quality models. Therefore, various approaches have been proposed in research and practice to partially or fully automate the creation of business process models. We conducted a systematic literature review (LR) on automatic generation of business process models. The LR demonstrates that there exist various approaches for automated generation of business process models, which differ in terms of the input data, generation methods, and modeling languages utilized. Despite active research into automatic model generation, there is still considerable scope for improvement. New technologies are continually being developed to support automatic model generation. Additionally, the increasing digitalization of processes and organizations generates vast amounts of data that can be harnessed for modeling.


Zugehörige Institution(en) am KIT Institut für Angewandte Informatik und Formale Beschreibungsverfahren (AIFB)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2024
Sprache Englisch
Identifikator ISBN: 978-3-031-50973-5
ISSN: 1865-1348
KITopen-ID: 1000167424
Erschienen in Business Process Management Workshops : BPM 2023 International Workshops, Utrecht, The Netherlands, September 11–15, 2023, Revised Selected Papers. Ed.: J. De Weerdt
Veranstaltung 21st International Conference on Business Process Management (BPM 2023), Utrecht, Niederlande, 11.09.2023 – 15.09.2023
Verlag Springer Nature Switzerland
Seiten 161–173
Serie Lecture Notes in Business Information Processing
Vorab online veröffentlicht am 11.01.2024
Nachgewiesen in Dimensions
Scopus
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