TY - GEN
T1 - Big Data Analysis for Predicting Future Skills
AU - Telukdarie, A.
AU - Munsamy, M.
AU - Gaula, M.
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
KW - Digital
KW - Skills prediction
UR - http://www.scopus.com/inward/record.url?scp=85125379841&partnerID=8YFLogxK
U2 - 10.1109/IEEM50564.2021.9673039
DO - 10.1109/IEEM50564.2021.9673039
M3 - Conference contribution
AN - SCOPUS:85125379841
T3 - 2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021
SP - 411
EP - 415
BT - 2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021
Y2 - 13 December 2021 through 16 December 2021
ER -
