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24 novembre 2021
- handle: 10670/1.fc7ibt
- isbn: 978-3-030-91278-9
- hal: hal-04323869
- doi: 10.1007/978-3-030-91279-6_2
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info:eu-repo/semantics/altIdentifier/doi/10.1007/978-3-030-91279-6_2
http://creativecommons.org/licenses/by/
Mots-clés
Enterprise modeling Assisted modeling Machine learning Graph neural networks Decision supportSujets proches
Molding (Clay, plaster, etc.) Clay modeling ModellingCiter ce document
Nikolay Shilov et al., « Machine Learning-Based Enterprise Modeling Assistance: Approach and Potentials », HAL-SHS : sciences de l'information, de la communication et des bibliothèques, ID : 10.1007/978-3-030-91279-6_2
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Résumé
Today, enterprise modeling is still a highly manual task that requires substantial human effort. Human modelers are not only assigned the creative component of the process, but they also need to perform routine work related to comparing the being developed model with the existing ones. Although the huge amount of information available today (big data) makes it possible to analyze more best practices, it also introduces difficulties since a person is often not able to analyze all of it. In this work, we analyze the potential of using machine learning methods for assistance during enterprise modeling. An illustrative case study proves the feasibility and potentials of the proposed approach, which can potentially significantly affect the modern modeling methods, and also has long-term prospects for the creation of new technologies, products, and services.