Abstract:

Most clustering algorithms have a difficulty in dealing with the cluster with arbitrarγshape and size , out-lier points and noises , as well as highly variable density. In order to overcome this difficulty , a clustering algorithm based on dynamic division of connected graph is proposed. In this algorithm , a l-connected graph of data set is firsi constructed , which is then divided with the strategy of dynamic division. Therefore , the data set is divided into se-veral disconnected subsets of connected graph , each of which forms a clustering. Experimental results show that the proposed algorithm is of great applicability because it can effectively solve the clustering problem of the cluster with arbitrarγshape and size , outlier points and noises , as well as highly variable density.

Key words: connected graph, clustering algorithm, dynamic division