Improved K-medoids Clustering Algorithm under Semantic Web

DOI

10.2991/iccsee.2013.185How to use a DOI?

Keywords

component, Ontology, Semantic Web, K-mediods algorithm

Abstract

K-medoids clustering algorithm is highly efficient in classifying cluster categories. Based on algorithm analysis and selection improvement of centre point K, this paper sets up a web model of ontology data set object. It tries to demonstrate through experiment evaluation that the improved algorithm can greatly enhance the accuracy of clustering results 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/).

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TY  - CONF
AU  - Wentian Ji
AU  - Qingju Guo
AU  - Sheng Zhong
AU  - En Zhou
PY  - 2013/03
DA  - 2013/03
TI  - Improved K-medoids Clustering Algorithm under Semantic Web
BT  - Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)
PB  - Atlantis Press
SP  - 731
EP  - 733
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccsee.2013.185
DO  - 10.2991/iccsee.2013.185
ID  - Ji2013/03
ER  -