An Agglomerative Hierarchical Clustering Algorithm Based on Weighted Representative Points
一种基于加权多代表点的层次聚类算法

As an agglomerative hierarchical clustering algorithm, CURE firstly employs the method of representing clusters by selecting some "representative points". Through the analysis of the feature of traditional hierarchical clus- tering algorithm, a novel agglomerative hierarchical clustering algorithm called WRPC is proposed in this paper. WR- PC can identify clusters with complex shapes and avrious size by introducing the influence-weight-based representative points selection mechanism and k-nearest-neighbor-method-based clusters nesting mechanim. Experimental results show that WRPC can provide better clustering result with high executing efficiency.