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» Using Dynamic Time Warping to Find Patterns in Time Series
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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...
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...
CSDA
2006
191views more  CSDA 2006»
13 years 4 months ago
Forecasting daily time series using periodic unobserved components time series models
We explore a periodic analysis in the context of unobserved components time series models that decompose time series into components of interest such as trend, seasonal and irregu...
Siem Jan Koopman, Marius Ooms
PKDD
2005
Springer
188views Data Mining» more  PKDD 2005»
13 years 10 months ago
Elastic Partial Matching of Time Series
We consider a problem of elastic matching of time series. We propose an algorithm that automatically determines a subsequence b of a target time series b that best matches a query ...
Longin Jan Latecki, Vasilis Megalooikonomou, Qiang...
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