Abstract
Changes in the skill requirements of occupations can alter the balance in the numbers of high, middle and low-skilled jobs on the market. This can result in structural unemployment, stagnating income and other unforeseen social and economic side effects. In this paper, we demonstrate the use of a recent matrix factorization technique for extracting the underlying skill categories from O*NET, a publicly available database on occupational skill requirements. This study builds upon earlier work which also focused on this database, and which indicated that changes in skill requirements were in response to increased automation which unevenly affected different segments of the job market. In this paper we refine the methodological underpinnings of the earlier work and report some preliminary results which already show great promise.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
References
Autor, D.H., Dorn, D.: How technology wrecks the middle class. The New York Times, 24 August 2013
MacCrory, F., Westerman, G., AlHammadi, Y., Brynjolfsson, E.: Racing with and against the machine: changes in occupational skill composition in an era of rapid technological advance. In: Proceedings of the International Conference on Information Systems - Building a Better World through Information Systems, ICIS 2014, Auckland, New Zealand, 14–17 December 2014
Baumol, W.J., Bowen, W.G.: Performing Arts-the Economic Dilemma: A Study of Problems Common to Theatre, Opera, Music and Dance. MIT Press, Cambridge (1966)
Acemoglu, D., Autor, D.: Skills, tasks and technologies: implications for employment and earnings. Handb. Labor Econ. 4, 1043–1171 (2011)
Autor, D., Levy, F., Murnane, R.: The skill content of recent technological change: an empirical exploration. Q. J. Econ. 118(4), 1279–1333 (2003)
Lee, D.D., Seung, H.S.: Algorithms for non-negative matrix factorization. In: Advances in Neural Information Processing Systems, pp. 556–562 (2001)
Xu, W., Liu, X., Gong, Y.: Document clustering based on non-negative matrix factorization. In: Proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in Informaion Retrieval, pp. 267–273. ACM (2003)
Liu, H., Wu, Z., Li, X., Cai, D., Huang, T.S.: Constrained nonnegative matrix factorization for image representation. IEEE Trans. Pattern Anal. Mach. Intell. 34(7), 1299–1311 (2012)
Acknowledgement
The authors would like to express their gratitude to the Masdar Institute of Science and Technology for supporting this research.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Woon, W.L., Aung, Z., AlKhader, W., Svetinovic, D., Omar, M.A. (2015). Changes in Occupational Skills - A Case Study Using Non-negative Matrix Factorization. In: Arik, S., Huang, T., Lai, W., Liu, Q. (eds) Neural Information Processing. ICONIP 2015. Lecture Notes in Computer Science(), vol 9491. Springer, Cham. https://doi.org/10.1007/978-3-319-26555-1_71
Download citation
DOI: https://doi.org/10.1007/978-3-319-26555-1_71
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-26554-4
Online ISBN: 978-3-319-26555-1
eBook Packages: Computer ScienceComputer Science (R0)