Big Data Analysis for Predicting Future Skills

A. Telukdarie, M. Munsamy, M. Gaula
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Abstract

The ability to predict skills of the future is fundamental in this rapidly changing global environment. The ability to predict and invest in the appropriate skills could prove to be a key differentiator for country specific growth. Global competitiveness, employment, technological investments, and social-economic dependencies are drivers to capacity development to predict future skills. The current approaches include a combination of expanding on current skill demand, adoption of economic indicators or survey-based forecasting. The challenge is the inclusion of future trends, specifically the ability to forecast new skills or combinations of existing skills. This research explores a novel method in adopting research publications to predict new/ undetermined skills requirements. This study downloads 700 000 papers, develops a multilayer data analysis protocol, screens and provides insights into the adoption of research publications analysis for the prediction of future skills.
预测未来技能的大数据分析
在这个快速变化的全球环境中,预测未来技能的能力至关重要。预测和投资于适当技能的能力可能证明是具体国家增长的关键区别因素。全球竞争力、就业、技术投资和社会经济依赖关系是预测未来技能的能力发展的驱动因素。目前的方法包括扩大当前的技能需求,采用经济指标或基于调查的预测。挑战在于包含未来趋势,特别是预测新技能或现有技能组合的能力。本研究探索了一种采用研究出版物来预测新的/不确定的技能需求的新方法。这项研究下载了70万篇论文,开发了一个多层数据分析协议,筛选并提供了对采用研究出版物分析预测未来技能的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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