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Effective Monotone Knowledge Integration in Kernel Support Vector Machines Read chapter Read first chapter

2016 | OriginalPaper | Chapter

Deriving Public Sector Workforce Insights: A Case Study Using Australian Public Sector Employment Profiles

Authors : Shameek Ghosh, Yi Zheng, Thorsten Lammers, Ying Ying Chen, Carolyn Fitzmaurice, Scott Johnston, Jinyan Li

Published in: Advanced Data Mining and Applications

Publisher: Springer International Publishing

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Abstract

Effective approaches for measurement of human capital in public sector and government agencies is essential for robust workforce planning against changing economic conditions. To this purpose, adopting innovative hypotheses driven workforce data analysis can help discover hidden patterns and trends about the workforce. These trends are useful for decision making and support the development of policies to reach desired employment outcomes. In this study, the data challenges and approaches to a real life workforce analytics scenario are described. Statistical results from numerous workforce data experiments are combined to derive three hypotheses that are useful to public sector organisations for human resources management and decision making.

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Metadata
Title
Deriving Public Sector Workforce Insights: A Case Study Using Australian Public Sector Employment Profiles
Authors
Shameek Ghosh
Yi Zheng
Thorsten Lammers
Ying Ying Chen
Carolyn Fitzmaurice
Scott Johnston
Jinyan Li
Copyright Year
2016
Book
Advanced Data Mining and Applications

Print ISBN: 978-3-319-49585-9

Electronic ISBN: 978-3-319-49586-6

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-49586-6_55

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