Tight bounds on the estimation distance using wavelet

Authors:
Bing Liu;Zhihui Wang;Jingtao Li;Wei Wang;Baile Shi
Affiliations:
Department of Computing and Information Technology, Fudan University, Shanghai, China;Department of Computing and Information Technology, Fudan University, Shanghai, China;Department of Computing and Information Technology, Fudan University, Shanghai, China;Department of Computing and Information Technology, Fudan University, Shanghai, China;Department of Computing and Information Technology, Fudan University, Shanghai, China
Venue:
WAIM '06 Proceedings of the 7th international conference on Advances in Web-Age Information Management
Year:
2006

Citing 9
Cited 1

Fast subsequence matching in time-series databases

SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
Wavelets for computer graphics: theory and applications

Wavelets for computer graphics: theory and applications
Approximate computation of multidimensional aggregates of sparse data using wavelets

SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Efficient Similarity Search In Sequence Databases

FODO '93 Proceedings of the 4th International Conference on Foundations of Data Organization and Algorithms
WaveCluster: a wavelet-based clustering approach for spatial data in very large databases

The VLDB Journal — The International Journal on Very Large Data Bases
Approximate query processing using wavelets

The VLDB Journal — The International Journal on Very Large Data Bases
Efficient Time Series Matching by Wavelets

ICDE '99 Proceedings of the 15th International Conference on Data Engineering
Extended wavelets for multiple measures

Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Similarity Search Over Time-Series Data Using Wavelets

ICDE '02 Proceedings of the 18th International Conference on Data Engineering

An Efficient Similarity Searching Algorithm Based on Clustering for Time Series

ICDM '08 Proceedings of the 8th industrial conference on Advances in Data Mining: Medical Applications, E-Commerce, Marketing, and Theoretical Aspects

Quantified Score

Hi-index	0.00

Visualization

Abstract

Time series similarity search is of growing importance in many applications. Wavelet transforms are used as a dimensionality reduction technique to permit efficient similarity search over high-dimensional time series data. This paper proposes the tight upper and lower bounds on the estimation distance using wavelet transform, and we show that the traditional distance estimation is only part of our lower bound. According to the lower bound, we can exclude more dissimilar time series than traditional method. And according to the upper bound, we can directly judge whether two time series are similar, and further reduce the number of time series to process in original time domain. The experiments have shown that using the upper and lower tight bounds can significantly improve filter efficiency and reduce running time than traditional method.