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» Fast approximate correlation for massive time-series data
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ICDE
2010
IEEE
188views Database» more  ICDE 2010»
14 years 4 months ago
Space-efficient Online Approximation of Time Series Data: Streams, Amnesia, and Out-of-order
In this paper, we present an abstract framework for online approximation of time-series data that yields a unified set of algorithms for several popular models: data streams, amnes...
Sorabh Gandhi, Luca Foschini, Subhash Suri
ICDM
2009
IEEE
121views Data Mining» more  ICDM 2009»
13 years 11 months ago
Finding Time Series Motifs in Disk-Resident Data
—Time series motifs are sets of very similar subsequences of a long time series. They are of interest in their own right, and are also used as inputs in several higher-level data...
Abdullah Mueen, Eamonn J. Keogh, Nima Bigdely Sham...
SSDBM
1999
IEEE
124views Database» more  SSDBM 1999»
13 years 9 months ago
An Indexing Scheme for Fast Similarity Search in Large Time Series Databases
We address the problem of similarity search in large time series databases. We introduce a novel indexing algorithm that allows faster retrieval. The index is formed by creating b...
Eamonn J. Keogh, Michael J. Pazzani
ECCV
2006
Springer
14 years 6 months ago
Learning Nonlinear Manifolds from Time Series
Abstract. There has been growing interest in developing nonlinear dimensionality reduction algorithms for vision applications. Although progress has been made in recent years, conv...
Ruei-Sung Lin, Che-Bin Liu, Ming-Hsuan Yang, Naren...
SIGMOD
2001
ACM
184views Database» more  SIGMOD 2001»
14 years 5 months ago
Locally Adaptive Dimensionality Reduction for Indexing Large Time Series Databases
Similarity search in large time series databases has attracted much research interest recently. It is a difficult problem because of the typically high dimensionality of the data....
Eamonn J. Keogh, Kaushik Chakrabarti, Sharad Mehro...