[1] XING Z, PEI J, KEOGH E. A brief survey on sequence classification[J]. ACM SIGKDD Explorations Newsletter, 2010, 12(1):40-48. [2] DONG G, PEI J. Sequence Data Mining[M]. Berlin:Springer, 2007:47-65. [3] 郭躬德,陈黎飞,李南.近邻分类方法及其应用[M].厦门:厦门大学出版社,2013:29-97.(GUO G D, CHEN L F, LI N. Nearest Neighbour Classification Method and Its Applications[M]. Xiamen:Xiamen University Press, 2013:29-97.) [4] CRISTIANINI N, SCHOLKOPF B. Support vector machines and kernel methods:the new generation of learning machines[J]. Artificial Intelligence, 2002, 23(3):31-41. [5] THEODORIDIS S. Machine Learning:A Bayesian and Optimization Perspective[M]. San Diego:Academic Press, 2015:876-902. [6] 敖丽敏,罗存金.基于神经网络集成的DNA序列分类方法研究[J].计算机仿真,2012,29(6):171-175.(AO L M, LUO C J. DNA series classification based on ensemble neural networks[J]. Computer Simulation, 2012, 29(6):171-175.) [7] 袁铭.标度曲线拟合与金融时间序列聚类[J].计算机应用,2015,34(11):3344-3347.(YUAN M. Fitting of scaling curve and financial time series clustering[J]. Journal of Computer Applications, 2015, 34(11):3344-3347.) [8] KELIL A, WANG S. SCS:A new similarity measure for categorical sequences[C]//Proceedings of the 8th IEEE International Conference on Data Mining. Washington, DC:IEEE Computer Society, 2008:343-352. [9] HERRANZ J, NIN J, SOLE M. Optimal symbol alignment dis-tance:a new distance for sequences of symbols[J]. IEEE Transactions on Knowledge and Data Engineering, 2011, 23(10):1541-1554. [10] YAKHNENKO O, SILVESCU A, HONAVAR V. Discriminatively trained Markov model for sequence classification[C]//Proceedings of the 5th IEEE International Conference on Data Mining. Washington, DC:IEEE Computer Society, 2005:498-505. [11] 杨一鸣,潘嵘,潘嘉林,等.时间序列分类问题的算法比较[J].计算机学报,2007,30(8):1259-1266.(YANG Y M, PAN R, PAN J L, et al. A comparative study on time series classification[J]. Chinese Journal of Computers, 2007, 30(8):1259-1266.) [12] KONDRAK G. N-gram similarity and distance[C]//Proceedings of the 12th International Conference on String Processing and Information Retrieval. Berlin:Springer, 2005:115-126. [13] FINK G A. Markov Models for Pattern Recognition:From Theory to Applications[M]. Berlin:Springer, 2008:95-111. [14] TSCHUMITSCHEW K, NAUCK D, KLAWONN F. A classifica-tion algorithm for process sequences based on Markov chains and Bayesian networks[C]//Proceedings of the 14th International Conference on Knowledge-based and Intelligent Information and Engineering Systems. Berlin:Springer, 2010:141-147. [15] 尹锐,李雄飞,李军,等.基于线性分段与HMM的时间序列分类算法[J].模式识别与人工智能,2011,24(4):574-581.(YIN R, LI X F, LI J, et al. Time series classification algorithm based on linear segmentation and HMM[J]. Pattern Recognition & Artificial Intelligence, 2011, 24(4):574-581.) [16] XIONG T, WANG S, JIANG Q, et al. A novel variable-order Markov model for clustering categorical sequences[J]. IEEE Transactions on Knowledge and Data Engineering, 2014, 26(10):2339-2353. [17] KARLIN S, GHANDOUR G. Comparative statistics for DNA and protein sequences:single sequence analysis[J]. Proceedings of the National Academy of Sciences, 1985, 82(17):5800-5804. [18] WEI D, JIANG Q, WEI Y, et al. A novel hierarchical clustering algorithm for gene sequences[J]. BMC Bioinformatics, 2012, 13(1):174. [19] LOISELLE S, ROUAT J, PRESSNITZER D, et al. Exploration of rank order coding with spiking neural networks for speech recognition[C]//Proceedings of the 2005 IEEE International Joint Conference on Neural Networks. Washington, DC:IEEE Computer Society, 2005:2076-2080. [20] NAMIKI Y, ISHIDA T, AKIYAMA Y. Acceleration of sequence clustering using longest common subsequence filtering[J]. BMC Bioinformatics, 2013, 14(Suppl 8):S7. |