State of the Art: Automatic Generation of Business Process Models-Reference-Cited by-同舟云学术

State of the Art: Automatic Generation of Business Process Models

Published:2024 Issue: Volume: Page:161-173
ISSN:1865-1348
Container-title:Lecture Notes in Business Information Processing
language:en
Short-container-title:

Author:

Schüler Selina^ORCID,Alpers Sascha^ORCID

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-50974-2_13

Reference33 articles.

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2. Adamo, G., Ghidini, C., Di Francescomarino, C.: What is a process model composed of?: a systematic literature review of meta-models in BPM. Softw. Syst. Model. 20(4), 1215–1243 (2021). https://doi.org/10.1007/s10270-020-00847-w

3. Bellan, P., Dragoni, M., Ghidini, C.: Leveraging pre-trained language models for conversational information seeking from text (2022). arXiv:2204.03542

4. Chadli, N., Kabbaj, M.I., Bakkoury, Z.: An improved ad hoc approach based on active help method to detect data flow anomalies in a loop of business process modeling. In: Proceedings of the 1st International Conference of Computer Science and Renewable Energies, Ouarzazate, Morocco, pp. 284–290. SCITEPRESS - Science and Technology Publications (2018). https://doi.org/10.5220/0009775402840290

5. Danenas, P., Skersys, T., Butleris, R.: Enhancing the extraction of SBVR business vocabularies and business rules from UML use case diagrams with natural language processing. In: Proceedings of the 23rd Pan-Hellenic Conference on Informatics, Nicosia Cyprus, pp. 1–8. ACM (2019). https://doi.org/10.1145/3368640.3368641

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