Abstract
In this paper, we propose dimensionality reduction representation of multi-scale time series histograms, which is performed based on the multi-scale histograms. It is a faster and efficient way to pre-select time sequence in a database and leads to reduce the need of time sequence comparisons when answering similarity queries. A new metric distance function MD ( ) that consistently lower-bounds WED and also satisfies the triangular inequality is also presented and based on it, we construct the Slim-tree index structure as the metric access method to answer similarity queries. We also extend it to subsequence matching and presented a MSST index structure.
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References
Agrawal, R., Faloutsos, C., Swami, A.N.: Efficient Similarity Search In Sequence Databases. In: Lomet, D.B. (ed.) FODO 1993. LNCS, vol. 730, pp. 69–84. Springer, Heidelberg (1993)
Yi, B.-K., Faloutsos, C.: Fast Time Sequence Indexing for Arbitrary Lp Norms. The VLDB Journal, 385–394 (2000)
Keogh, E.J., Chakrabarti, K., Pazzani, M.: Dimensionality Reduction for Fast Similarity Search In Large Time Series Databases. The VLDB Journal, 490–501 (1995)
Perng, C.-S., Wang, H., Zhang, S.R., Stott Parker, D.: Landmarks: A New Model for Similarity-Based Pattern Querying In Time Series Databases. In: ICDE, pp. 33–42 (2000)
Chen, L., Tamer Ozsu, M.: Similarity-Based Retrieval of Time-Series Data Using Multi- Scale Histograms. Technical Report CS-2003-31 (September 2003)
Berman, A., Shapiro, L.G.: Selecting Good Keys for Triangle-Inequality-Based Pruning Algorithms. In: Intl. Workshop on Content-Based Access of Image and Video Databases (CAIVD 1998), Bombay, India (1998)
Keogh, E., Chakrabarti, K., Pazzani, M., Mehrotra: Dimensionality Reduction for Fast Similarity Search in Large Time Series Databases. Journal of Knowledge and Information Systems, 263–286
Traina Jr., C., Traina, A.J.M., Seeger, B., Faloutsos, C.: Slim-Trees: High Performance Metric Trees Minimizing Overlap Between Nodes. In: Intl. Conf. on Extending Database Technology, Konstanz, Germany (2000)
Santos, R.F., Filho, Traina, A.J.M., Traina Jr., C., Faloutsos, C.: Similarity Search without Tears: The OMNI Family of All-purpose Access Methods. In: IEEE ICDE, Heidelberg, Germany (2001)
Kahveci, T., Singh, T.: Variable length queries for time series data. In: ICDE, Heidelberg, Germany (2001)
Ng, R., Tam, D.: Multi-level Filtering for High-dimensional Image Data: Why and How. IEEE Trans. Knowledge & Data Engineering (December 1999)
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© 2004 Springer-Verlag Berlin Heidelberg
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Liu, JW., Yu, SJ., Le, JJ. (2004). The Dimension-Reduced Multi-scale Histogram: A New Method for Fast and Efficient Retrieval of Similar Time Sequences and Subsequence. In: Li, Q., Wang, G., Feng, L. (eds) Advances in Web-Age Information Management. WAIM 2004. Lecture Notes in Computer Science, vol 3129. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-27772-9_6
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DOI: https://doi.org/10.1007/978-3-540-27772-9_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22418-1
Online ISBN: 978-3-540-27772-9
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