Mining complex time-series data by learning Markovian models

Proceedings - IEEE International Conference on Data Mining, ICDM

Volumn , Issue , 2006, Pages 1136-1140

  Wang, Yi ^a   Zhou, Lizhu ^a   Feng, Jianhua ^a   Wang, Jianyong ^a   Liu, Zhi Qiang ^b  

^a TSINGHUA UNIVERSITY   (China)

^b CITY UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

[No Author keywords available]

Indexed keywords

3D MOTION CAPTURE DATA; TOPOLOGY GRAPHS; VARIABLE-LENGTH HIDDEN MARKOV MODEL (VLHMM);

DATA MINING; GRAPH THEORY; HIDDEN MARKOV MODELS; LEARNING SYSTEMS; MOTION ESTIMATION; PATTERN RECOGNITION; THREE DIMENSIONAL COMPUTER GRAPHICS;

TIME SERIES ANALYSIS;

EID: 84865626510     PISSN: 15504786     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDM.2006.105     Document Type: Conference Paper

References (15)

1. W. G. Aref, M. G. Elfeky, and A. K. Elmagarmid. Incremental, online, and merge mining of partial periodic patterns in time-series databases. IEEE Trans. Knowledge and Data Engineering, 16(3):332-342, 2004.
2. P. Bühlmann and A. J. Wyner. Variable length Markov chains. Annals of Statistics, 27:480-513, 1999.
3. T. Corman, C. Leiserson, and R. Rivest. Introduction to Algorithms. MIT Press, Cambridge, MA, 1990.
4. M. G. Elfeky, W. G. Aref, and A. K. Elmagarmid. Periodicity detection in time series databases. IEEE Trans. Knowledge and Data Engineering, 17(7):875-887, 2005.
5. C. P. Gabor, K. J. Supowit, and W.-L. Hsu. Recognizing circle graphs in polynomial time. Journal of the ACM, 36(3):435-473, 1989.
6. J.-W. Han, G.-Z. Dong, and Y.-W. Yin. Efficient mining of partial periodic patterns in time series database. In IEEE ICDE, pages 106-115, March 1999.
7. J.-W. Han and M. Kamber. Data Mining: Concepts and Techniques. Morgan Kaufmann, 2000.
8. S. Ma and J. L. Hellerstein. Mining partially periodic even patterns with unknown periods. In IEEE ICDE, pages 205-214, April 2001.
9. J.-F. Mari, D. Fohr, and J.-C. Junqira. A second-order HMM for high performance word and phoneme-based continuous speech recognition. In IEEE International Conference on Acoustics, Speech, and Signal Processing, 1996.
10. E. Nuutila and E. Soisalon-Soininen. On finding the strongly connected components in a directed graph. Information Processing Letters, 49:9-14, 1993.
11. L. R. Rabiner. A tutorial on hidden markov models and selected applications in speech recognition. Proc. IEEE, 77(2):257-286, 1989.
12. D. Ron, Y. Singer, and N. Tishby. The power of Amnesia: Learning probabilistic automata with variable memory length. Machine Learning, 25(2-3):117-149, 1996.
13. C. Sheng, W. Hsu, and M. L. Lee. Mining dense periodic patterns in time series data. In IEEE ICDE, pages 115-115, April 2005.
14. R. E. Tarjan. Depth-first search and linear graph algorithms. SIAM Journal on Computing, 1(2):146-160, 1972.
15. Y. Wang. Mining complex time-series data by learning markovian models. Technical report, Department of Computer Science, Tsinghua University. http://dbgroup.cs.tsinghua.edu.en/wangyi/motion-engine/icdm.pdf, 2006.