The Improvement of K-Medoids Clustering Algorithm under Semantic Web
Wen Tian Ji, Qing Ju Guo, Sheng Zhong · Applied Mechanics and Materials · 2013
K-medoids clustering algorithm is an efficient algorithm in classifying cluster categories. Based on algorithm analysis, this paper first improves the selection of K center point and then sets up a web model of ontology data set object with the aim of demonstrating through experiment evaluation that the improved algorithm can greatly enhance the accuracy of clustering results under semantic web.