Efficient Retrieval of Similar Time Sequences Under Time Warping
ICDE '98 Proceedings of the Fourteenth International Conference on Data Engineering
An Index-Based Approach for Similarity Search Supporting Time Warping in Large Sequence Databases
Proceedings of the 17th International Conference on Data Engineering
Efficient Searches for Similar Subsequences of Different Lengths in Sequence Databases
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
Exact indexing of dynamic time warping
Knowledge and Information Systems
Scaling and time warping in time series querying
The VLDB Journal — The International Journal on Very Large Data Bases
Speeding Up Similarity Search on a Large Time Series Dataset under Time Warping Distance
PAKDD '09 Proceedings of the 13th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
Faster retrieval with a two-pass dynamic-time-warping lower bound
Pattern Recognition
Probabilistic Similarity Search for Uncertain Time Series
SSDBM 2009 Proceedings of the 21st International Conference on Scientific and Statistical Database Management
A simple approximation for dynamic time warping search in large time series database
IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
Time series classification by class-specific Mahalanobis distance measures
Advances in Data Analysis and Classification
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Dynamic Time Warping (DTW) has been widely used for measuring the distance between the two time series, but its computational complexity is too high to be directly applied to similarity search in large databases. In this paper, we propose a new approach to deal with this problem. It builds the filtering process based on histogram distance, using mean value to mark the trend of points in every segment and counting different binary bits to select the candidate sequences. Therefore, it produces a more appropriate collection of candidates than original binary histograms in less time, guaranteeing no false dismissals. The results of simulation experiments prove us that the new method exceeds the original one.