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基于改进分段半马尔可夫模型的在线序列模式检测*

, PP. 505-511

Keywords: 在线序列模式检测,隐马尔可夫模型,分段半马尔可夫模型

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Abstract:

在时间序列数据挖掘中,在线检测在时间上存在任意缩放的相似模式是一个具有挑战性的问题.本文对基于模型匹配的分段半马尔可夫模型进行改进,通过引入偏移量分布、振幅差值分布和前项状态,克服该模型参数难以确定、鲁棒性差的缺点.实验表明,改进分段半马尔可夫模型能够快速准确检测出在时间上存在任意缩放的相似模式.

References

[1]  Faloutsos C, Ranganathan M, Manolopoulos Y. Fast Subsequence Matching in TimeSeries Databases // Proc of the ACM SIGMOD International Conference on Management of Data. Minneapolis, USA, 1994: 419429
[2]  Keogh E J, Pazzani M J. A Simple Dimensionality Reduction Technique for Fast Similarity Search in Large Time Series Databases // Proc of the 4th PacificAsia Conference on Knowledge Discover and Data Mining. Kyoto, Japan, 2000: 122133
[3]  Ge X P, Smyth P. Deformable Markov Model Templates for TimeSeries Pattern Matching // Proc of the 6th ACM SIGKDD International Conference on Knowledge Discover and Data Mining. Boston, USA, 2000: 8190
[4]  Meek C, Birmingham W P. The Dangers of Parsimony in QuerybyHumming Applications // Proc of the 4th International Symposium on Music Information Retrieval. Baltimore, USA, 2003: 5156
[5]  Keogh E, Palpanas T, Zordan V B, et al. Indexing Large HumanMotion Databases // Proc of the 30th International Conference on Very Large Data Bases. Toronto, Canada, 2004: 780791
[6]  Mandelbrot B B. Fractals and Scaling in Finance: Discontinuity, Concentration, Risk. New York, USA: SpringerVerlag, 2000
[7]  Fu A W, Keogh E, Lau L Y H, et al. Scaling and Time Warping in Time Series Querying // Proc of the 31st International Conference on Very Large Data Bases. Trondheim, Norway, 2005: 649660
[8]  Argyros T, Ermopoulos C. Efficient Subsequence Matching in Time Series Databases under Time and Amplitude Transformations // Proc of the 3rd IEEE International Conference on Data Mining. Melbourne, USA, 2003: 481484
[9]  Rabiner L R, Rosenberg A E, Levinson S E. Considerations in Dynamic Time Warping Algorithms for Discrete Word Recognition. IEEE Trans on Acoustics, Speech and Signal Processing, 1978, 26(6): 575582
[10]  Baum L E, Petrie T. Statistical Inference for Probabilistic Functions of Finite State Markov Chains. Annual of Mathematical Statistics, 1966, 37(6): 15541563
[11]  Rabiner L R. A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition. Proc of the IEEE, 1989, 77(2): 257286
[12]  Ferguson J D. Variable Duration Models for Speech // Proc of the Symposium on the Application of Hidden Markov Models to Text and Speech. Princeton, USA, 1980: 143179
[13]  Ostendorf M, Digalakis V V, Kimball O A. From HMM's to Segmental Model: a Unified View of Stochastic Modeling for Speech Recognition. IEEE Trans on Speech and Audio Processing, 1996, 4(5): 360378
[14]  Ge X P, Smyth P. Hidden Markov Models for Endpoint Detection in Plasma Etch Processes. Technical Report, UCIICS 0154, Irvine, USA: University of California. Department of Information and Computer Science, 2001
[15]  Jia Sen, Qian Yuntao, Dai Guang. An Advance Segmental SemiMarkov Model Based Online Series Pattern Detection // Proc of the 17th International Conference on Pattern Recognition. Cambridge, UK, 2004, Ⅲ: 634  637

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