Yang Jia-Hai, Wu Jian-Ping, An Chang-Qing. Internet Measurement Theory and Its Applications. Beijing: Post & Telecom Press, 2009. 383-408 (杨家海, 吴建平, 安常青. 互联网络测量理论与应用. 北京: 人民邮电出版社, 2009. 383-408)
[2]
Moore A W, Papagiannaki K. Toward the accurate identification of network applications. In: Proceedings of the 2005 Passive and Active Network Measurement. Boston, MA: Springer, 2005: 41-54
[3]
Santos A, Fernandes S, Antonello R, Szabo G, Lopes P, Sadok D. High-performance traffic workload architecture for testing DPI systems. In: Proceedings of the 2011 IEEE Global Telecommunications Conference (GLOBECOM 2011). Houston, TX: IEEE, 2011. 1-5
[4]
Roughan M, Sen S, Spatscheck O, Duffield N. Class-of-service mapping for QoS: a statistical signature-based approach to IP traffic classification. In: Proceedings of the 4th ACM SIGCOMM Internet Measurement Conference. Taormina, Sicily, Italy: ACM, 2004. 135-148
[5]
Erman J, Mahanti A, Arlitt M, Cohen I, Williamson C. Offline/realtime traffic classification using semi-supervised learning. Performance Evaluation, 2007, 64(9-12): 1194-1213
[6]
Zhang J, Tuo X G, Yuan Z, Chen H F. Analysis of fMRI data using an integrated principal component analysis and supervised affinity propagation clustering approach. IEEE Transactions on Biomedical Engineering, 2011, 58(11): 3184-3196
[7]
Liu H W. Community detection by affinity propagation with various similarity measures. In: Proceedings of the 4th International Joint Conference on Computational Sciences and Optimization. Yunnan, China: IEEE, 2011. 182-186
[8]
Bilenko M, Basu S, Mooney R J. Integrating constraints and metric learning in semi-supervised clustering. In: Proceedings of the 21st International Conference on Machine Learning. New York, USA: ACM, 2004. 81-88
[9]
Liu Sheng-Lan, Yan De-Qin. A new global embedding algorithm. Acta Automatica Sinica, 2011, 37(7): 828-835 (刘胜蓝, 闫德勤. 一种新的全局嵌入降维算法. 自动化学报, 2011, 37(7): 828-835)
[10]
Yang W K, Sun C Y, Zhang L. A multi-manifold discriminant analysis method for image feature extraction. Pattern Recognition, 2011, 44(8): 1648-1657
[11]
Yan De-Qin, Liu Sheng-Lan, Li Yan-Yan. An embedding dimension reduction algorithm based on sparse analysis. Acta Automatica Sinica, 2011, 37(11): 1306-1312 (闫德勤, 刘胜蓝, 李燕燕. 一种基于稀疏嵌入分析的降维方法. 自动化学报, 2011, 37(11): 1306-1312)
[12]
Mitzenmacher M, Upfal E. Probability and Computing: Randomized Algorithm and Probabilistic Analysis. Cambridge, U.K.: Cambridge University Press, 2005. 44-45
[13]
Karagiannis T, Broido A, Faloutsos M, Claffy K C. Transport layer identification of P2P traffic. In: Proceedings of the 4th ACM SIGCOMM on Internet Measurement. New York, USA: ACM, 2004. 121-134
[14]
Antonello R, Fernandes S, Sadok D, Kelner J. Characterizing signature sets for testing DPI systems. In: Proceedings of the 2011 IEEE GLOBECOM Workshops. Houston, TX: IEEE, 2011. 678-683
[15]
Zander S, Nguyen T, Armitage G. Automated traffic classification and application identification using machine learning. In: Proceedings of the 30th IEEE Conference on Local Computer Networks. Sydney, Australia: IEEE, 2005. 250-257
[16]
Moore A W, Zuev D. Internet traffic classification using Bayesian analysis techniques. In: Proceedings of the 2005 Internet Traffic Classification Using Bayesian Analysis Techniques (SIGMETRICS). Alberta, Canada: ACM, 2005. 50-60
[17]
Frey B J, Dueck D. Clustering by passing messages between data points. Science, 2007, 315(5814): 972-976
[18]
He Y C, Chen Q C, Wang X L, Xu R F, Bai X H, Meng X J. An adaptive affinity propagation document clustering. In: Proceedings of the 7th International Conference on Information and System. Cairo, Egypt: IEEE, 2010. 1-7
[19]
Wagstaf K, Cardie C. Clustering with instance-level constraints. In: Proceedings of the 17th International Conference on Machine Learning. Stanford, USA: Morgan Kaufmann Publishers, 2000. 1103-1110
[20]
Seung H S, Lee D D. The manifold ways of perception. Science, 2000, 290(5500): 2268-2269
[21]
Zhang S W, Lei Y K. Modified locally linear discriminant embedding for plant leaf recognition. Neurocomputing, 2011, 74(14-15): 2284-2290
[22]
Zhang J P, Wang X D, Krger U, Wang F Y. Principal curve algorithms for partitioning high-dimensional data spaces. IEEE Transactions on Neural Networks, 2011, 22(3): 367-380
[23]
Thedoridis S, Koutroumbas K. Pattern Recognition (3rd edition). Beijing: Publishing House of Electronics Industry, 2010. 389-407
[24]
Moore A W. Moore Set [Online], available: http://www.cl. cam.ac.uk/research/srg/netos/nprobe/data/papsers/sigme- trics/index.html. 2012