Ensuring sustainable growth based on the artificial intelligence analysis and forecast of in-demand skills

Author:

Vankevich Alena,Kalinouskaya Iryna

Abstract

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.

Publisher

EDP Sciences

Reference18 articles.

1. Labor and employment in the Republic of Belarus, Minsk, National Statistical Committee of the Republic of Belarus (2020)

2. Statistical Bulletin, 146 (2020)

3. Youth unemployment in frontier regions: the experience of comparative analysis, 157 (2017)

4. Makovskaia N.V., Transformation of labor processes in the course of modernization of enterprises, 144 (2015)

Cited by 11 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

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3