An all pairs shortest path algorithm with expected time O(n2logn)
SIAM Journal on Computing
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital Image Processing
Density-Based Multiscale Data Condensation
IEEE Transactions on Pattern Analysis and Machine Intelligence
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
BORDER: Efficient Computation of Boundary Points
IEEE Transactions on Knowledge and Data Engineering
A novel multiseed nonhierarchical data clustering technique
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Using cluster skeleton as prototype for data labeling
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Survey of clustering algorithms
IEEE Transactions on Neural Networks
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In this paper, a new framework for data analysis based on the "key points" in data distribution is proposed. Here, the key points contain three types of data points: bridge points, border points, and skeleton points, where our main contribution is the bridge points. For each type of key points, we have developed the corresponding detection algorithm and tested its effectiveness with several synthetic data sets. Meanwhile, we further developed a new hierarchical clustering algorithm SPHC (Skeleton Point based Hierarchical Clustering) to demonstrate the possible applications of the key points acquired. Based on some real-world data sets, we experimentally show that SPHC performs better compared with several classical clustering algorithms including Complete-Link Hierarchical Clustering, Single-Link Hierarchical Clustering, KMeans, Ncut, and DBSCAN.