Improved K-medoids Clustering Algorithm under Semantic Web

摘要：

　　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.

关键词： component Ontology Semantic Web K-mediods algorithm

作者: Ji Wentian Guo Qingju Zhong Sheng Zhou En

作者单位: Department of Software Engineering Hainan College of Software Technology Qionghai,China College of Information Science & Technology Hainan University Haikou,China

会议类型: 国际会议

会议名称: 2013 2nd International Conference on Computer Science and Electronics Engineering(ICCSEE2013)(2013年第二届计算机科学与电子工程国际会议)

会议地点: 杭州

会议语种:英文

页码: 731-733

在线出版日期: 2013-03-22（万方平台首次上网日期，不代表论文的发表时间）