Abstract
The paper presents the use of deep learning models to support the automation of management in IT projects on the example of task assignment. Managing IT projects is a complex process that requires the coordination of multiple tasks, resources, and individuals involved in the project. For this purpose, datasets were created to simulate various project environments, and models based on the GraphSAGE architecture were trained, enabling efficient modeling of relationships between tasks and programmers. It was observed that improving data quality could significantly enhance the performance of the models, suggesting the potential for further development and improvements in this area.
Paper Type
Full Paper
DOI
10.62036/ISD.2025.3
Automation of Selected Processes in IT Project Management with Natural Language Processing
The paper presents the use of deep learning models to support the automation of management in IT projects on the example of task assignment. Managing IT projects is a complex process that requires the coordination of multiple tasks, resources, and individuals involved in the project. For this purpose, datasets were created to simulate various project environments, and models based on the GraphSAGE architecture were trained, enabling efficient modeling of relationships between tasks and programmers. It was observed that improving data quality could significantly enhance the performance of the models, suggesting the potential for further development and improvements in this area.
Recommended Citation
Poniszewska-Maranda, A., Wawrzynkiewicz, P. & Ochelska-Mierzejewska, J. (2025). Automation of Selected Processes in IT Project Management with Natural Language ProcessingIn I. Luković, S. Bjeladinović, B. Delibašić, D. Barać, N. Iivari, E. Insfran, M. Lang, H. Linger, & C. Schneider (Eds.), Empowering the Interdisciplinary Role of ISD in Addressing Contemporary Issues in Digital Transformation: How Data Science and Generative AI Contributes to ISD (ISD2025 Proceedings). Belgrade, Serbia: University of Gdańsk, Department of Business Informatics & University of Belgrade, Faculty of Organizational Sciences. ISBN: 978-83-972632-1-5. https://doi.org/10.62036/ISD.2025.3