Proceedings of the 2016 International Conference on Education, Management and Computer Science

Application and Research on an Improved Clustering Method in Teaching Evaluation

Authors
Shaorong Feng
Corresponding Author
Shaorong Feng
Available Online May 2016.
DOI
https://doi.org/10.2991/icemc-16.2016.220How to use a DOI?
Keywords
Teaching evaluation; Weight; K-medoids clustering; Evaluation index; Teaching quality
Abstract
In order to analyze the teaching evaluation data effectively, based on the diversity of the weight of different evaluation indexes, this paper focuses on the issue of the current evaluation index weight setting, the method of combined weight distribution is proposed. In order to improve the accuracy of clustering, the weight is introduced to the nearest neighbor K-medoids clustering algorithm. The experimental results of UCI data set and the teaching evaluation data show that the proposed algorithm is feasible and effective in the teaching evaluation data analysis.
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This is an open access article distributed under the CC BY-NC license.

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Volume Title
Proceedings of the 2016 International Conference on Education, Management and Computer Science
Series
Advances in Intelligent Systems Research
Publication Date
May 2016
ISBN
978-94-6252-202-2
ISSN
1951-6851
DOI
https://doi.org/10.2991/icemc-16.2016.220How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Shaorong Feng
PY  - 2016/05
DA  - 2016/05
TI  - Application and Research on an Improved Clustering Method in Teaching Evaluation
BT  - Proceedings of the 2016 International Conference on Education, Management and Computer Science
PB  - Atlantis Press
SP  - 1138
EP  - 1144
SN  - 1951-6851
UR  - https://doi.org/10.2991/icemc-16.2016.220
DO  - https://doi.org/10.2991/icemc-16.2016.220
ID  - Feng2016/05
ER  -