[1] Xu R, Wunsch D. Survey of Clustering Algorithms. IEEE Transaction on Neural Networks, 2005, 16(3): 645-678.
[2] Han J, Kamber M. Data Mining: Concepts and Techniques, Second Edition. Morgan Kaufmann, San Francisco, 2006.
[3] Filippone M, Camastra F, Masulli F, Rovetta S. A Survey of Kernel and Spectral Methods for Clustering. Pattern Recognition, 2008, 41(1): 176-190.
[4] 张莉,周伟达,焦李成. 核聚类算法. 计算机学报, 2002, 25(6): 587-590.
[5] Burges C J C. A Tutorial on Support Vector Machines for Pattern Recognition. Data Mining and Knowledge Discovery, 1998, 2(2): 121-167.
[6] Tax D M J, Duin R P W. Support Vector Domain Description. Pattern Recognition Letters, 1999, 20(11-13): 1191-1199.
[7] Ben-Hur A, Horn D, Siegelmann H T, Vapnik V. Support Vector Clustering. Journal of Machine Learning Research, 2001, 2(12): 125-137.
[8] Scholkopf B, Williamson R, Smola A, Shawe-Taylor J, Platt J. Support Vector Method for Novelty Detection. Advances in Neural Information Processing System 12. 2000: 582-588.
[9] 吕常魁,姜澄宇,王宁生. 一种支持向量聚类的快速算法. 华南理工大学学报. 2005, 33(1): 6-9.
[10] Lee J, Lee D. An Improved Cluster Labeling Method for Support Vector Clustering. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2005, 27(3): 461-464.
[11] Camastra F, Verri A. A Novel Kernel Method for Clustering. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2005, 27(5):801-805.