Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)

The Analysis of the Ontology-based K-Means Clustering Algorithm

Authors
Qingju Guo, Wentian Ji, Sheng Zhong, En Zhou
Corresponding Author
Qingju Guo
Available Online March 2013.
DOI
10.2991/iccsee.2013.186How to use a DOI?
Keywords
component, Ontology, Semantic Web, Data, K-means Algorithm
Abstract

In view of research findings made from home and abroad on clustering algorithm and the traditional partition clustering method K-means algorithm, this paper first analyses the advantages and disadvantages of this algorithm and then combines it with ontology- based data set to establish a semantic web model. It then tries to improve the existing clustering algorithm in various constraint conditions to demonstrate that the improved algorithm has better efficiency and accuracy under semantic web.

Copyright
© 2013, 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/).

Download article (PDF)

Volume Title
Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)
Series
Advances in Intelligent Systems Research
Publication Date
March 2013
ISBN
10.2991/iccsee.2013.186
ISSN
1951-6851
DOI
10.2991/iccsee.2013.186How to use a DOI?
Copyright
© 2013, 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  - Qingju Guo
AU  - Wentian Ji
AU  - Sheng Zhong
AU  - En Zhou
PY  - 2013/03
DA  - 2013/03
TI  - The Analysis of the Ontology-based K-Means Clustering Algorithm
BT  - Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)
PB  - Atlantis Press
SP  - 734
EP  - 737
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccsee.2013.186
DO  - 10.2991/iccsee.2013.186
ID  - Guo2013/03
ER  -