Extracting Decision Model and Notation models from text using deep learning techniques-Reference-Cited by-同舟云学术

Extracting Decision Model and Notation models from text using deep learning techniques

Published:2023-01 Issue: Volume:211 Page:118667
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Goossens Alexandre^ORCID,De Smedt Johannes^ORCID,Vanthienen Jan^ORCID

Funder

Fonds Wetenschappelijk Onderzoek

KU Leuven

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference56 articles.

1. Abadeer, M. (2020). Assessment of DistilBERT performance on Named Entity Recognition task for the detection of Protected Health Information and medical concepts. In Proceedings of the 3rd clinical natural language processing workshop (pp. 158–167).

2. Comparative analyses of Bert, Roberta, Distilbert, and Xlnet for text-based emotion recognition;Adoma,2020

3. Improving the reliability of deep neural networks in NLP: A review;Alshemali;Knowledge-Based Systems,2020

4. Business process mining from group stories;de AR Goncalves,2009

5. Natural language techniques supporting decision modelers;Arco;Data Mining and Knowledge Discovery,2021

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. POI recommendation for occasional groups Based on hybrid graph neural networks;Expert Systems with Applications;2024-03

2. Towards Taming Large Language Models with Prompt Templates for Legal GRL Modeling;Lecture Notes in Business Information Processing;2024

3. Deriving Decision Mining System Capabilities: A Research Agenda;36th Bled eConference – Digital Economy and Society: The Balancing Act for Digital Innovation in Times of Instability: June 25 – 28, 2023, Bled, Slovenia, Conference Proceedings;2023-12-12

4. Comparing the Performance of GPT-3 with BERT for Decision Requirements Modeling;Cooperative Information Systems;2023-10-25

5. TAG: UML Activity Diagram Deeply Supervised Generation from Business Textural Specification;2023 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER);2023-03