The aim of clustering is to help people find and recognize the unknown world

so as to accumulate knowledge for us in real life. Clustering analysis is an important part for the majority of researchers in unsupervised leaning

and is usually used as an analysis tool to explore the unknown data and its regularity for many cross subjects. It analyzed the procedure of clustering

and briefly surveyed the related achievements. Moreover

the problems of clustering algorithms in processing various data types

high dimensional data

unbalanced data were concluded

and the expansibility and the selection of evaluation index for algorithms were also discussed in detail. At last

some directions for future research were proposed. The above work can give valuable reference to further studies of clustering and data mining.