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» Scaling up Dynamic Time Warping to Massive Dataset
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PKDD
1999
Springer
90views Data Mining» more  PKDD 1999»
13 years 9 months ago
Scaling up Dynamic Time Warping to Massive Dataset
Eamonn J. Keogh, Michael J. Pazzani
SDM
2012
SIAM
285views Data Mining» more  SDM 2012»
11 years 7 months ago
A Novel Approximation to Dynamic Time Warping allows Anytime Clustering of Massive Time Series Datasets
Given the ubiquity of time series data, the data mining community has spent significant time investigating the best time series similarity measure to use for various tasks and dom...
Qiang Zhu 0002, Gustavo E. A. P. A. Batista, Thana...
KDD
2012
ACM
205views Data Mining» more  KDD 2012»
11 years 7 months ago
Searching and mining trillions of time series subsequences under dynamic time warping
Most time series data mining algorithms use similarity search as a core subroutine, and thus the time taken for similarity search is the bottleneck for virtually all time series d...
Thanawin Rakthanmanon, Bilson J. L. Campana, Abdul...
KDD
2000
ACM
168views Data Mining» more  KDD 2000»
13 years 8 months ago
Scaling up dynamic time warping for datamining applications
There has been much recent interest in adapting data mining algorithms to time series databases. Most of these algorithms need to compare time series. Typically some variation of ...
Eamonn J. Keogh, Michael J. Pazzani
PAKDD
2010
ACM
189views Data Mining» more  PAKDD 2010»
13 years 9 months ago
Subsequence Matching of Stream Synopses under the Time Warping Distance
In this paper, we propose a method for online subsequence matching between histogram-based stream synopsis structures under the dynamic warping distance. Given a query synopsis pat...
Su-Chen Lin, Mi-Yen Yeh, Ming-Syan Chen