Proceedings of the 3rd International Conference on Wireless Communication and Sensor Networks (WCSN 2016)

Application of the Data Mining in the University Human Resource Management

Authors
Li Yi, Wei-Xin Yao
Corresponding Author
Li Yi
Available Online December 2016.
DOI
10.2991/icwcsn-16.2017.111How to use a DOI?
Keywords
Data mining; Human Resource; Maximal tree.
Abstract

Competitions among different universities are the competition of talents. The content is about how to obtain talents, how to properly allocate talents, how to comprehensively obtain information of human resources and promote the level of human resource management of universities. The paper used cluster analysis and decision tree, etc tools tries to solve problems existed in the university human resource management such as talents division, brain drain by using data mining tools. Through the reference case, the paper uses ten teachers' data as example, extracts information from hidden information and comes to the conclusion on teacher talent division; the conclusion can help the use and allocation for talents in universities and colleges.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 3rd International Conference on Wireless Communication and Sensor Networks (WCSN 2016)
Series
Advances in Computer Science Research
Publication Date
December 2016
ISBN
10.2991/icwcsn-16.2017.111
ISSN
2352-538X
DOI
10.2991/icwcsn-16.2017.111How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Li Yi
AU  - Wei-Xin Yao
PY  - 2016/12
DA  - 2016/12
TI  - Application of the Data Mining in the University Human Resource Management
BT  - Proceedings of the 3rd International Conference on Wireless Communication and Sensor Networks (WCSN 2016)
PB  - Atlantis Press
SP  - 551
EP  - 554
SN  - 2352-538X
UR  - https://doi.org/10.2991/icwcsn-16.2017.111
DO  - 10.2991/icwcsn-16.2017.111
ID  - Yi2016/12
ER  -