Changes in occupational skills - A case study using non-negative matrix factorization

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

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.

Original languageBritish English
Title of host publicationNeural Information Processing - 22nd International Conference, ICONIP 2015, Proceedings
EditorsTingwen Huang, Qingshan Liu, Weng Kin Lai, Sabri Arik
PublisherSpringer Verlag
Pages627-634
Number of pages8
ISBN (Print)9783319265544
DOIs
StatePublished - 2015
Event22nd International Conference on Neural Information Processing, ICONIP 2015 - Istanbul, Turkey
Duration: 9 Nov 201512 Nov 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9491
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference22nd International Conference on Neural Information Processing, ICONIP 2015
Country/TerritoryTurkey
CityIstanbul
Period9/11/1512/11/15

Keywords

  • Data mining
  • Empirical research
  • Job characteristics
  • Non-negative matrix factorization
  • Source separation

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