Abstract
There has been a lot of interest in matching and retrieval of similar time sequences in time series databases. Most of previous work is concentrated on similarity matching and retrieval of time sequences based on the Euclidean distance. However, the Euclidean distance is sensitive to the absolute offsets of time sequences. In addition, the Euclidean distance is not a suitable similarity measurement in terms of shape. In this paper, we propose an indexing scheme for efficient matching and retrieval of time sequences based on the minimum distance. The minimum distance can give a better estimation of similarity in shape between two time sequences. Our indexing scheme can match time sequences of similar shapes irrespective of their vertical positions and guarantees no false dismissals. We experimentally evaluated our approach on real data(stock price movement).
This work was supported by the Brain Korea 21 Project in 2001
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
R. Agrawal, T. Imielinski and A. Swami: Database Mining: A Performance Perspective. IEEE TKDE, Special issue on Learning and Discovery in Knowledge-Based Databases 5–6(1993) 914–925
Usama M. Fayyad, Gregory Piatetsky-Shapiroa and Padhraic Smyth: Knowledge Discovery and Data Mining: Towards a Unifying Framework. In Proc. of the Second International Conference on Knowledge Discovery and Data Mining(1996) 82–88
A. Guttman: R-trees: A Dynamic Index Structure for Spatial Searching. In Proc. of SIGMOD Conference on Management of Data(1984) 47–57
Rakesh Agrawal, Christos Faloutsos and Arun N. Swami: Efficient Similarity Search In Sequence Databases. In Proc. of International Conference on Foundations of Data Organization and Algorithms(1993) 69–84
Christos Faloutsos, M. Ranganathan and Yannis. Manolopoulos: Fast Subsequence Matching in Time-Series Databases. In Proc. of SIGMOD Conference on Management of Data(1994) 419–429
Davood Rafiei, Alberto O. Mendelzon: Efficient Retrieval of Similar Time Sequences Using DFT. In Proc. of International Conference on Foundations of Data Organization and Algorithms(1998)
Kelvin Kam Wing Chu, Sze Kin Lam and Man Hon Wong: An Efficient Hash-Based Algorithm for Sequence Data Searching. The Computer Journal 41–6(1998) 402–415
Kin-pong Chan, Ada Wai-chee Fu: Efficient Time Series Matching by Wavelets. In Proc. of International Conference on Data Engineering(1999) 126–133
Dina Q. Goldin, Paris C. Kanellakis: On Similarity Queries for Time-Series Data: Constraint Specification and Implementation. In Proc. of International Conference on Principles and Practice of Constraint Programming(1995) 137–153
Chung-Sheng Li, Philip S. Yu and Vittorio Castelli: HierarchyScan: A Hierarchical Similarity Search Algorithm for Databases of Long Sequences. In Proc. of International Conference on Data Engineering(1996) 546–553
Davood Rafiei, Alberto O. Mendelzon: Similarity-Based Queries for Time Series Data. In Proc. of SIGMOD Conference on Management of Data(1997) 13–25
Gautam Das, Dimitrios Gunopulos and Heikki Mannila: Finding Similar Time Series. In Proc. of European Conference on Principles of Data Mining and Knowledge Discovery(1997) 88–100
Byoung-Kee Yi, H. V. Jagadish and Christos Faloutsos: Efficient Retrieval of Similar Time Sequences Under Time Warping. In Proc. of International Conference on Data Engineering(1998) 201–208
Sze Kin Lam, Man Hon Wong: A Fast Projection Algorithm for Sequence Data Searching. Data and Knowledge Engineering 28–3(1998) 321–339
Kelvin Kam Wing Chu, Man Hon Wong: Fast Time-Series Searching with Scaling and Shifting. In Proc. of Symposium on Principles of Database Systems(1999) 237–248
Davood Rafiei: On Similarity-Based Queries for Time-Series Data. In Proc. of International Conference on Data Engineering(1999) 410–417
Eamonn J. Keogh, Michael J. Pazzani: A Simple Dimensionality Reduction Technique for Fast Similarity Search in Large Time Series Databases. In Proc. of Pacific-Asia Conference on Knowledge Discovery and Data Mining(2000) 122–133
Sanghyun Park, Wesley W. Chu, Jeehee Yoon and Chihcheng Hsu: Efficient Searches for Similar Subsequences of Different Lengths in Sequence Databases. In Proc. of International Conference on Data Engineering(2000) 23–32
Byoung-Kee Yi, Christos Faloutsos: Fast Time Sequence Indexing for Arbitrary Lp Norms. In Proc. of International Conference on Very Large Data Bases(2000) 385–394
Eamonn J. Keogh, Kaushik Chakrabarti, Sharad Mehrotra and Michael J. Pazzani: Locally Adaptive Dimensionality Reduction for Indexing Large Time Series Databases. In Proc. of SIGMOD Conference on Management of Data(2001) 151–162
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2002 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Lee, S., Kwon, D., Lee, S. (2002). Efficient Pattern Matching of Time Series Data. In: Hendtlass, T., Ali, M. (eds) Developments in Applied Artificial Intelligence. IEA/AIE 2002. Lecture Notes in Computer Science(), vol 2358. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48035-8_57
Download citation
DOI: https://doi.org/10.1007/3-540-48035-8_57
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-43781-9
Online ISBN: 978-3-540-48035-8
eBook Packages: Springer Book Archive