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» Online summarization of dynamic time series data
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88
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ICDM
2003
IEEE
240views Data Mining» more  ICDM 2003»
15 years 2 months ago
Clustering of Time Series Subsequences is Meaningless: Implications for Previous and Future Research
Given the recent explosion of interest in streaming data and online algorithms, clustering of time series subsequences, extracted via a sliding window, has received much attention...
Eamonn J. Keogh, Jessica Lin, Wagner Truppel
ICDE
2011
IEEE
237views Database» more  ICDE 2011»
14 years 1 months ago
Creating probabilistic databases from imprecise time-series data
— Although efficient processing of probabilistic databases is a well-established field, a wide range of applications are still unable to benefit from these techniques due to t...
Saket Sathe, Hoyoung Jeung, Karl Aberer
NN
2010
Springer
225views Neural Networks» more  NN 2010»
14 years 7 months ago
Learning to imitate stochastic time series in a compositional way by chaos
This study shows that a mixture of RNN experts model can acquire the ability to generate sequences that are combination of multiple primitive patterns by means of self-organizing ...
Jun Namikawa, Jun Tani
87
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ASC
2008
14 years 9 months ago
Info-fuzzy algorithms for mining dynamic data streams
Most data mining algorithms assume static behavior of the incoming data. In the real world, the situation is different and most continuously collected data streams are generated by...
Lior Cohen, Gil Avrahami, Mark Last, Abraham Kande...
DEXA
2009
Springer
167views Database» more  DEXA 2009»
15 years 4 months ago
Alignment of Noisy and Uniformly Scaled Time Series
The alignment of noisy and uniformly scaled time series is an important but difficult task. Given two time series, one of which is a uniformly stretched subsequence of the other, w...
Constanze Lipowsky, Egor Dranischnikow, Herbert G&...