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» On Clustering Multimedia Time Series Data Using K-Means and ...
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MUE
2007
IEEE
190views Multimedia» more  MUE 2007»
12 years 4 months ago
On Clustering Multimedia Time Series Data Using K-Means and Dynamic Time Warping
After the generation of multimedia data turned digital, an explosion of interest in their data storage, retrieval, and processing has drastically increased. This includes videos, ...
Vit Niennattrakul, Chotirat Ann Ratanamahatana
SDM
2012
SIAM
285views Data Mining» more  SDM 2012»
10 years 6 days 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...
ICCS
2007
Springer
12 years 4 months ago
Inaccuracies of Shape Averaging Method Using Dynamic Time Warping for Time Series Data
Shape averaging or signal averaging of time series data is one of the prevalent subroutines in data mining tasks, where Dynamic Time Warping distance measure (DTW) is known to work...
Vit Niennattrakul, Chotirat Ann Ratanamahatana
KDD
2012
ACM
205views Data Mining» more  KDD 2012»
10 years 7 days 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...
KES
2005
Springer
12 years 3 months ago
Using Relevance Feedback to Learn Both the Distance Measure and the Query in Multimedia Databases
Much of the world’s data is in the form of time series, and many other types of data, such as video, image, and handwriting, can easily be transformed into time series. This fact...
Chotirat (Ann) Ratanamahatana, Eamonn J. Keogh
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