Symbolization of time-series: An evaluation of SAX, Persist, and ACA

Proceedings - 4th International Congress on Image and Signal Processing, CISP 2011

Volumn 4, Issue , 2011, Pages 2223-2228

  Sant'Anna, Anita ^a   Wickstrom, Nicholas ^a  

^a HALMSTAD UNIVERSITY   (Sweden)

Author keywords

[No Author keywords available]

Indexed keywords

EXPERIMENTAL DATA; PERIODIC SIGNAL; RANDOM SIGNAL; SIGNAL CHARACTERISTIC; TEMPORAL DOMAIN; TEMPORAL PATTERN; TWO DOMAINS;

ELECTRICAL ENGINEERING;

SIGNAL PROCESSING;

EID: 84855591065     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CISP.2011.6100559     Document Type: Conference Paper

References (31)

1. C. S. Daw, C. E. A. Finney, and E. R. Tracy, "A review of symbolic analysis of experimental data," Review of Scientific Instruments, vol. 74, no. 2, p. 915, 2003.
2. H.-H. Bock and E. Diday, Analysis of symbolic data : exploratory methods for extracting statistical information from complex data. Springer, 2000.
3. K.-S. Leung, K. H. Lee, J.-F. Wang, E. Ng, H. Chan, S. Tsui, T. Mok, P.-H. Tse, and J.-Y. Sung, "Data mining on dna sequences of hepatitis b virus," Computational Biology and Bioinformatics, IEEE/ACM Transactions on, vol. 8, no. 2, pp. 428-440, 2011.
4. W. Fan, M. Gordon, and P. Pathak, "Discovery of context-specific ranking functions for effective information retrieval using genetic programming,"IEEE Transactions on Knowledge and Data Engineering, vol. 16, no. 4, pp. 523-527, 2004.
5. N. Leone, G. Pfeifer, W. Faber, T. Eiter, G. Gottlob, S. Perri, and F. Scarcello, "The dlv system for knowledge representation and reasoning,"ACM Transactions on Computational Logic, vol. 7, pp. 499-562, 2006. (Pubitemid 44330485)
6. D. Nadeau and S. Sekine, "A survey of named entity recognition and classification," Lingvisticae Investigationes, vol. 30, pp. 3-26.
7. J. Lin, E. Keogh, L. Wei, and S. Lonardi, "Experiencing SAX: a novel symbolic representation of time series," Data Mining and Knowledge Discovery, vol. 15, pp. 107-144, 2007. (Pubitemid 47293484)
8. F. Mörchen, A. Ultsch, and O. Hoos, "Extracting interpretable muscle activation patterns with time series knowledge mining,"International Journal of Knowledge-based and Intelligent Engineering Systems, vol. 9, pp. 197-208, 2005. [Online]. Available: http: //portal.acm.org/citation.cfm?id= 1233864.1233868
9. G. Guerra-Filho and Y. Aloimonos, "A language for human action,"Computer, vol. 40, no. 5, pp. 42-51, 2007.
10. A. Zinnen, K. V. Laerhoven, and B. Schiele, "Toward recognition of short and non-repetitive activities from wearable sensors," in AmI-07: European Conference on Ambient Intelligence, 2007, pp. 142-158.
11. F. Zhou, F. Torre, and J. Hodgins, "Aligned cluster analysis for temporal segmentation of human motion," in 8th IEEE International Conference on Automatic Face Gesture Recognition, 2008, pp. 1-7.
12. A. Sant'Anna and N. Wickström, "A symbol-based approach to gait analysis from acceleration signals: Identification and detection of gait events and a new measure of gait symmetry," IEEE Transactions on Information Technology in Biomedicine, vol. 14, no. 5, pp. 1180-1187, 2010.
13. E. Keogh, K. Chakrabarti, M. Pazzani, and S. Mehrotra, "Locally adaptive dimensionality reduction for indexing large time series databases,"SIGMOD Record, vol. 30, pp. 151-162, 2001.
14. H. André-Jönsson and D. Badal, "Using signature files for querying time-series data," in Principles of Data Mining and Knowledge Discovery, ser. Lecture Notes in Computer Science, J. Komorowski and J. Zytkow, Eds. Springer Berlin / Heidelberg, 1997, vol. 1263, pp. 211-220. (Pubitemid 127097506)
15. Y.-W. Huang and P. S. Yu, "Adaptive query processing for time-series data," in Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, 1999, pp. 282-286.
16. H. Shimodaira, K.-I. Noma, M. Nakai, and S. Sagayama, "Dynamic time-alignment kernel in support vector machine," in Advances in Neural Information Processing Systems, vol. 2, 2001, pp. 921-928.
17. B. Schölkopf, A. Smola, and K.-R. Müller, "Nonlinear component analysis as a kernel eigenvalue problem," Neural Computation, vol. 10, no. 5, pp. 1299-1319, 1998. (Pubitemid 128463674)
18. D. Pham and A. Chan, "Control chart pattern recognition using a new type of self organizing neural network," Journal of Process Mechanical Engineering, pp. 115-127, 1998.
19. E. Keogh, X. Xi, L. Wei, and C. A. Ratanamahatana, "The UCR Time Series Classification/Clustering Homepage," http://www.cs.ucr. edu/~eamonn/time-series-data, 2006.
20. K. Van Laerhoven and A. Aronsen, "Memorizing what you did last week: Towards detailed actigraphy with a wearable sensor." in 27th International Conference on Distributed Computing Systems Workshops, IEEE Computer Society. IEEE Computer Society, 2007, p. 47.
21. "Darmstad technical university, embedded sensing systems - walk8-gait dataset," http://www.ess.tu-darmstadt.de/datasets/walk8-gait.
22. "physiologic signal archives for biomedical research," http://www. physionet.org/physiobank/database/.
23. "Bureau of economic analysis - regional economic accounts," http:// www.bea.gov/regional/spi/.
24. F. Mörchen and O. Hoos, "Inline skating EMG data," Philipps-University Marburg, Germany.
25. "The Quality of Life Grand Challenge Data Collection: Kitchen," http: //kitchen.cs.cmu.edu/main.php.
26. "Cmu graphics lab motion capture database," http://mocap.cs.cmu.edu/.
27. "U.s. census bureau," http://www.census.gov/population/.
28. Y. Cai and R. Ng, "Indexing spatio-temporal trajectories with chebyshev polynomials," in Proceedings of the 2004 ACM SIGMOD international conference on Management of data. ACM, 2004, pp. 599-610.
29. "Symbolic aggregate approximation homepage," http://www.cs.ucr.edu/~eamonn/SAX.htm.
30. "Persist time series discretization," http://www.mybytes.de/ persist.php.
31. "Aligned cluster analysis's software," http://www.humansensing. cs.cmu. edu/aca/code.html.