Abstract
This paper reports the results of empirical evaluation of the dissimilarity measure for time-series multiscale matching. In order to investigate fundamental characteristics of the dissimilarity measure, we performed quantitative analysis of the induced dissimilarities using simple sine wave and its variants, and compared them with dissimilarities obtained by dynamic time warping. The results showed that differences on the amplitude, phase and trends were respectively captured by the terms on rotation angle, phase and gradient, although they also showed weakness on the linearity.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Keogh, E.: Mining and Indexing Time Series Data. In: Tutorial at the 2001 IEEE International Conference on Data Mining (2001)
Hirano, S., Tsumoto, S.: Mining Similar Temporal Patterns in Long Timeseries Data and Its Application to Medicine. In: Proceedings of the IEEE 2002 International Conference on Data Mining, pp. 219–226 (2002)
Mokhtarian, F., Mackworth, A.K.: Scale-based Description and Recognition of planar Curves and Two Dimensional Shapes. IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI-8(1), 24–43 (1986)
Ueda, N., Suzuki, S.: A Matching Algorithm of Deformed Planar Curves Using Multiscale Convex/Concave Structures. IEICE Transactions on Information and Systems J73-D-II(7), 992–1000 (1990)
Berndt, D.J., Clifford, J.: Using dynamic time warping to find patterns in time series. In: Proceedings of AAAI Workshop on Knowledge Discovery in Databases, pp. 359–370 (1994)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Hirano, S., Tsumoto, S. (2003). Empirical Evaluation of Dissimilarity Measures for Time-Series Multiscale Matching. In: Zhong, N., Raś, Z.W., Tsumoto, S., Suzuki, E. (eds) Foundations of Intelligent Systems. ISMIS 2003. Lecture Notes in Computer Science(), vol 2871. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39592-8_64
Download citation
DOI: https://doi.org/10.1007/978-3-540-39592-8_64
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-20256-1
Online ISBN: 978-3-540-39592-8
eBook Packages: Springer Book Archive