| Issue |
E3S Web Conf.
Volume 208, 2020
First Conference on Sustainable Development: Industrial Future of Territories (IFT 2020)
|
|
|---|---|---|
| Article Number | 03060 | |
| Number of page(s) | 7 | |
| Section | Sustainable Economy | |
| DOI | https://doi.org/10.1051/e3sconf/202020803060 | |
| Published online | 24 November 2020 | |
Ensuring sustainable growth based on the artificial intelligence analysis and forecast of in-demand skills
Vitebsk State Technological University, Moskovsky Ave., 72, 210038 Vitebsk, Republic of Belarus
* Corresponding author: vankevich_ev@tut.by
Sustainable economic growth requires a system for forecasting the in-demand skills and competencies. The existing methods of analysis and forecasting of the labor market use truncated databases based on surveys of employers or registered vacancies on the state portal, which do provide reliable forecasts of the required competencies for the education system to ensure their timely formation. It is also impossible to analyze the need in terms of competencies, and not the number of employees. Therefore, a more reliable source of data is the analysis of vacancies and resumes collected by scraping from online job portals, which allows you to analyze vacancies and resumes in the context of the described competencies, and develop a forecast of their dynamics. The article presents an algorithm for using artificial intelligence in the analysis and forecasting of skills and competencies in demand, the advantages of which lie not only in the volume and speed of the processed information, but also in ensuring the quality and comparability of data.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.