Big Data-based Solutions for Sustainable Digital Services: Evaluation of Research Methods

2022 63rd International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS 2022): Proceedings 2022
Guntis Mosāns, Jānis Kampars

Modern information technology infrastructure is highly complex, and its monitoring requires the integration of different monitoring tools and management systems. This is especially important for businesses that must be able to provide their digital services in crisis situations, such as the COVID-19 pandemic. This paper identifies research methods suitable to evaluate algorithms for integrated processing of graphs and vertex metrics in data streams. They are identified by means of a literature review. The research finding will serve as an input for further research activities on methods and technological solutions that enable the creation of resilient digital services that are able to adapt to changing contexts and crises, combining big data analysis, knowledge management, business data, and knowledge ecosystems.

Atslēgas vārdi
digital services | graphs | machine learning
DOI
10.1109/ITMS56974.2022.9937095
Hipersaite
https://ieeexplore.ieee.org/document/9937095

Mosāns, G., Kampars, J. Big Data-based Solutions for Sustainable Digital Services: Evaluation of Research Methods. No: 2022 63rd International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS 2022): Proceedings, Latvija, Riga, 6.-7. oktobris, 2022. Piscataway: IEEE, 2022, 1.-6.lpp. ISBN 979-8-3503-9986-8. e-ISBN 979-8-3503-9985-1. ISSN 2771-6953. e-ISSN 2771-6937. Pieejams: doi:10.1109/ITMS56974.2022.9937095

Publikācijas valoda
English (en)