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/).
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 -