ZPGuiGroupWhu/ClusteringDirectionCentrality

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Clustering by measuring local direction centrality for data with heterogeneous density and weak connectivity (CDC) We propose a novel Clustering algorithm by measuring Direction Centrality (CDC) locally. It adopts a density-independent metric based on the distribution of K-nearest neighbors (KNNs) to distinguish between internal and boundary points. The boundary points generate enclosed cages to bind the connections of internal points, thereby preventing cross-cluster connections and separating weakly-connected...