[1] Agrawal R, Gehrke J, Gunopulos D, et al. Automatic subspace clustering of high dimensionating data for data mining applications [C]. Proceedings of the 1998 ACM SIGMOD international conference on Management of data, ACM Press, 1998: 94-105.

[2] Agrawal R, Gehrke J, Gunopulos D, et al. Automatic subspace clustering of high dimensional data [J]. Data Mining and Knowledge Discovery, 2005, 11(1): 5-33.

[3] Cheng Chunhung, Fu Ada Waichee, Zhang Yi. Entropy-based subspace clustering for mining numerical data [C]. Proceedings of the 5th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, USACM Press, 1999: 84-93.

[4] Goil S, Nagesh H S, Choudhary A. MAFIA: Efficient and scalable subspace clustering for very large data sets [R]. Technique Report No. CPDC-TR-9906-010, Center for Parallel and Distributed Computing, Dept of Electrical and Computer Engineering. Northwestern University: Evanston IL, 1999.

[5] Aggarwal C C, Procopiuc C. Fast algorithms for projected clustering [C]. Proceedings of the 1999 ACM SIGMOD international conference on Management of data, ACM Press, 1999: 61-72.

[6] Gan G, Wu J. A convergence theorem for the fuzzy subspace clustering (FSC) algorithm [J]. Pattern Recognition, 2008, 41(6): 1939-1947.

[7] Frigui H, Nasraoui O. Simultaneous clustering and attribute discrimination [C]. The 9th IEEE International Conference on Fuzzy Systems, 2000.

[8] Huang J Z, Ng M K, Rong H, et al. Automated variable weighting in k-means type clustering [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005, 27(5): 657-668.

[9] Jing L, Ng M K, Huang J Z. An entropy weigh K-means algorithm for subspace clustering of highdimensional sparse data [J]. IEEE Transactions on Knowledge and Data Engineering, 2007, 19(8): 1-16.

[10] Chen Xiaojun, Ye Yunming, Xu Xiaofei, et al. A feature group weighting method for subspace clustering of high-dimensional data [J]. Pattern Recognition, 2012, 45(1): 434-446.

[11] Niu Kun, Zhang Shubo, Chen Junliang. Subspace clustering through attribute clustering [J]. Journal of Beijing University of Posts and Telecommunications (北京邮电大学学报), 2007, 30(3): 1(in Chinese).

[12] Zhu Lin, Lei Jingsheng, Bi Zhongqin, Yangjie. Soft subspace clustering algorithm for streaming data [J]. Journal of Software (软件学报), 2013, 24(11): 2610-2627 (in Chinese).

[13] Hu Zhengping, Li Jing. Face recognition of joint sparse representation based on low-rank subspace recovery [J]. Acta Electronica Sinica (电子学报), 2013, 5(5): 987-991 (in Chinese).

[14] Wang Jun, Wang Shitong, Dengzhao. A novel text clustering algorithm based on feature weighting distance and soft subspace learning [J]. Chinese Journal of Computers (计算机学报), 2012, 8(8): 1655-1665 (in Chinese).

[15] Li tao, Wang Weiwei, Zhai Dong, et al. Weighted-sparse subspace clustering method for image segmentation [J]. Journal of Systems Engineering and Electronics (系统工程与电子技术) 2014, 3(3): 580-585 (in Chinese).

[16] Deng Z H, Choi K S, Chung F L. Enhanced soft subspace clustering integrating with incluster and between-cluster information [J]. Pattern Recognition, 2012, 3(3): 767-781.

[17] Frey J, Dueck D. Clustering by passing messages between data points [J]. Science, 2007, 315(5814): 972-976.

[18] Jia S, Qian Y t, Ji Z. Band selection for hyperspectral imagery using affinity propagation [C]. Proceedings of the 2008 Digital Image Computing: Techniques and Applications, Canberra, 2008: 137-141.

[19] Li G, Guo L, Liu T M, et al. Grouping of brain MR images via affinity propagation [C]. IEEE International Symposium on Circuits and Systems, 2009: 2425-2428.

[20] Dueck D, Frey B J, Jojic N, et al. Constructing treatment portfolios using affinity propagation [C]. Proceedings of 12th Annual International Conference, RECOMB 2008, Berlin: Springer, 2008: 360-371.

[21] Shi Lin, Wang Defeng, Liu Wen. Automatic detection of arterial input function in dynamic contrast enhanced MRI based on affinity propagationclustering: Detection of AIF in DCE-MRI using AP clustering [J]. Journal of Magnetic Resonance Imaging, 2015, 39(5): 27-37.

[22] Lu Cheng, Song Shiji, Wu Cheng. K nearest neighbor intervals based AP clustering algorithm for large incomplete data [J]. Mathematical Problems in Engineering, 2015, 2015(5864): 1-9.

[23] Li Qiang, Shen Dong, Wang Fei. MQAM modulation recognition based on AP clustering method C [C]. MATEC Web of Conferences, 2016, 44(1): 01002.