Abstract: Traditional partition clustering algorithm can't discover clusters of arbitrary shapes.For this problem,a new path-based similarity measure is proposed,which can reflect the similarity between samples effectively.A new objective criterion function is designed which can show that one sample is more similar to another from the same cluster than that from a different cluster.Experimental results show that the proposed method can get better clustering results than k-means algorithm.