Student Management Based on Rough Set and Clustering

DOI

10.2991/icsnce-16.2016.97How to use a DOI?

Keywords

Student management; Rough set; Cluster; K-means

Abstract

The credit system makes teaching students in accordance with their aptitude possible, that provide the basis for the development of students' personality. At the same time, it has brought great challenges for the management of the students. In order to better manage the students, and to provide some useful guidance, K-means algorithm is used to cluster the students to the nearest classifications; rough set is used to reduce attributes in order to improve the efficiency of clustering. The method is applied to cluster students, and the result shows that it is feasible.

Copyright

© 2016, 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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TY  - CONF
AU  - Xueli Ren
AU  - Yubiao Dai
PY  - 2016/07
DA  - 2016/07
TI  - Student Management Based on Rough Set and Clustering
BT  - Proceedings of the 2016 International Conference on Sensor Network and Computer Engineering
PB  - Atlantis Press
SP  - 496
EP  - 500
SN  - 2352-5401
UR  - https://doi.org/10.2991/icsnce-16.2016.97
DO  - 10.2991/icsnce-16.2016.97
ID  - Ren2016/07
ER  -