Clustering algorithm research advances on data mining
Huiling Lu · Computer Engineering and Applications Journal · 2012
Clustering analysis is one of important research branches in data mining.Clustering criterion,similarity degree are illustrated;five kinds of traditional clustering algorithms are summarized,and their latest developments are pointed out;according to attribution ralation of the sample,sample data pre-processing,similarity measure of sample,sample update strategy,high-dimension of sample and integration with other disciplines,there are more than 20 clustering algorithms are explained and summarized,such as granular clustering,uncertainty clustering,quantum clustering,kernel clustering,spectral clustering,clustering ensemble,concept clustering,spherical shell clustering,affinity propagation clustering.That is a good summary and of positive significance for the clustering.