Abdulsalam H, Skillicorn D B, Martin P. Classification Using Streaming Random Forests. IEEE Trans on Knowledge and Data Engineering, 2011, 23(1): 22-36
[2]
Masud M M, Chen Qing, Khan L, et al. Addressing Concept Evolution in Concept-Drifting Data Streams // Proc of the 10th IEEE International Conference on Data Mining. Sydney, Australia, 2010: 929-934
[3]
Woo H J, Lee W S. EstMax: Tracing Maximal Frequent Item Sets Instantly over Online Transactional Data Streams. IEEE Trans on Knowledge and Data, 2008, 21(10): 1418-1431
[4]
Aggarwal C C, Han Jiawei, Wang Jianyong, et al. A Framework for Clustering Evolving Data Streams // Proc of the 29th International Conference on Very Large Data Bases. Berlin, Germany, 2003: 81-102
[5]
Masud M M, Gao J, Khan L, et al. A Practical Approach to Classify Evolving Data Streams: Training with Limited Amount of Labeled Data // Proc of the 8th IEEE International Conference on Data Mining. Pisa, Italy, 2008: 929-934
[6]
Kranen P, Assent I, Baldauf C, et al. Self-Adaptive Anytime Stream Clustering // Proc of the 9th IEEE International Conference on Data Mining. Miami, USA, 2009: 249-258
[7]
Cao Feng, Ester M, Qian Weining, et al. Density-Based Clustering over an Evolving Data Stream with Noise // Proc of the SIAM Conference on Data Mining. Bethesda, USA, 2006: 328-339
[8]
Chen Yixin, Tu Li. Density-Based Clustering for Real-Time Stream Data // Proc of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. San Jose, USA, 2007: 133-142
[9]
Heinz C, Seeger B. Cluster Kernels: Resource-Aware Kernel Density Estimators over Streaming Data. IEEE Trans on Knowledge and Data Engineering, 2008, 20(7): 880-893
[10]
Rodrigues P P, Gama J, Pedroso J P. Hierarchical Clustering of Time-Series Data Streams. IEEE Trans on Knowledge and Data Engineering, 2008, 20(5): 615-627
[11]
Ho S S, Wechsler H. A Martingale Framework for Detecting Changes in Data Streams by Testing Exchangeability. IEEE Trans on Pattern Analysis and Machine Intelligence, 2010, 32(12): 2113-2127
[12]
Papadimitriou S, Sun Jimeng, Faloutsos C. Streaming Pattern Discovery in Multiple Time-Series // Proc of the 31st International Conference on Very Large Data Bases. Trondheim, Norway, 2005: 697-708
[13]
Sakurai Y, Papadimitriou S, Faloutsos C. BRAID: Stream Mining through Group Lag Correlations // Proc of the ACM SIGMOD International Conference on Management of Data. Baltimore, USA, 2005: 599-610
[14]
Yang J. Dynamic Clustering of Evolving Streams with a Single Pass // Proc of the 19th International Conference on Data Engineering. Bangalore, India, 2003: 695-697
[15]
Beringer J, Hullermeier E. Online Clustering of Parallel Data Streams. Data Mining and Knowledge Discovery, 2006, 58(2): 180-204
[16]
Dai Biru, Huang J W, Yeh M Y, et al. Adaptive Clustering for Multiple Evolving Streams. IEEE Trans on Knowledge and Data Engineering, 2006, 18(9): 1166-1180
[17]
Deng Julong. Elements on Grey Theory. Wuhan, China: Huazhong University of Science and Technology Press, 2002 (in Chinese)(邓聚龙.灰理论基础.武汉:华中科技大学出版社, 2002)
[18]
Zhang Qishan. Difference Information Theory of Grey Hazy Set. Beijing, China: Petroleum Industry Press, 2002 (in Chinese)(张岐山.灰朦胧集的差异信息理论.北京:石油工业出版社, 2002)
[19]
Wang Qingyin, Zhao Xiuheng. The Relational Analysis of C-Mode. Journal of Huazhong University of Science and Technology, 1999, 27(3): 75-77 (in Chinese)(王清印,赵秀恒.C型关联分析.华中理工大学学报, 1999, 27(3): 75-77 )
[20]
Tang Wuxiang. The Concept and the Computation Method of Ts Correlation Degree. Application of Statistics and Management, 1995, 14(1): 34-37 (in Chinese)(唐五湘.T型关联度及其计算方法.数理统计与管理, 1995, 14(1): 34-37 )
[21]
Sun Yugang, Dang Yaoguo. Improvement on Grey T s Correlation Degree. System Engineering-Theory Practice, 2008, 28(4): 135-139 (in Chinese)(孙玉刚,党耀国.灰色T型关联度的改进.系统工程理论与实践, 2008, 28(4): 135-139)
[22]
Liu Sifeng, Xie Naiming. The Theory and the Application of Grey System. 4th Edition. Beijing, China: Science Press, 2008 (in Chinese)(刘思峰,谢乃明.灰色系统理论及其应用.第4版.北京:科学出版社, 2008)
[23]
Wang Zhengxin, Dang Yaoguo, Cao Mingxia. Weighted Degree of Grey Incidence Based on Optimized Entropy. System Engineering and Electronics, 2010, 32(4): 774-776 (in Chinese)(王正新,党耀国,曹明霞.基于灰熵优化的加权灰色关联度.系统工程与电子技术, 2010, 32(4): 774-776)
[24]
Wang Jingcheng, Zhu Wenzhi, Zhang Yanbin. Improved Algorithm of Grey Incidence Degree Based on Area. System Engineering and Electronics, 2010, 32(4): 777-779 (in Chinese)(王靖程,诸文智,张彦斌.基于面积的改进灰关联度算法.系统工程与电子技术, 2010, 32(4): 777-779)
[25]
Tu Li, Chen Ling, Zou Lingjun. Clustering Multiple Data Streams Based on Correlation Analysis. Journal of Software, 2009, 20(7): 1756-1767(in Chinese)(屠 莉,陈 崚,邹凌君.基于相关分析的多数据流聚类.软件学报, 2009, 20(7): 1756-1767)
