{"title":"Big Data Analysis for Predicting Future Skills","authors":"A. Telukdarie, M. Munsamy, M. Gaula","doi":"10.1109/IEEM50564.2021.9673039","DOIUrl":null,"url":null,"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.","PeriodicalId":6818,"journal":{"name":"2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","volume":"101 1","pages":"411-415"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEEM50564.2021.9673039","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
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.