Machine learning for enterprise modeling assistance: an investigation of the potential and proof of concept

Author:

Shilov NikolayORCID,Othman WalaaORCID,Fellmann MichaelORCID,Sandkuhl KurtORCID

Funder

Russian Science Foundation

Publisher

Springer Science and Business Media LLC

Subject

Modeling and Simulation,Software

Reference87 articles.

1. Riss, U.V., Maus, H., Javaid, S., Jilek, C.: Digital twins of an organization for enterprise modeling. In: PoEM 2020: The Practice of Enterprise Modeling. Lecture Notes in Business Information Processing, pp 25–40. Springer (2020)

2. Weske, M., Decker, G., Dumas, M., et al.: Model collection of the business process management academic initiative. https://zenodo.org/record/3758705 (2020). Accessed 8 Aug 2022

3. Fayoumi, A.: Toward an adaptive enterprise modelling platform. Lect. Notes Bus. Inf. Process. 335, 362–371 (2018). https://doi.org/10.1007/978-3-030-02302-7_23

4. Awadid, A., Bork, D., Karagiannis, D., Nurcan, S.: Toward generic consistency patterns in multi-view enterprise modelling. In: ECIS 2018 Proceedings, p 146. Association for Information Systems (AIS) (2018)

5. Fellmann, M., Koschmider, A., Laue, R., et al.: Business process model patterns: classification and repository of published work. In: EMISA 2019. Bonn, pp 67–75 (2020)

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