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» Fast algorithms for time series mining
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KDD
2004
ACM
210views Data Mining» more  KDD 2004»
15 years 10 months ago
Visually mining and monitoring massive time series
Moments before the launch of every space vehicle, engineering discipline specialists must make a critical go/no-go decision. The cost of a false positive, allowing a launch in spi...
Jessica Lin, Eamonn J. Keogh, Stefano Lonardi, Jef...
ICDM
2005
IEEE
271views Data Mining» more  ICDM 2005»
15 years 3 months ago
HOT SAX: Efficiently Finding the Most Unusual Time Series Subsequence
In this work, we introduce the new problem of finding time series discords. Time series discords are subsequences of a longer time series that are maximally different to all the r...
Eamonn J. Keogh, Jessica Lin, Ada Wai-Chee Fu
KDD
2002
ACM
182views Data Mining» more  KDD 2002»
15 years 10 months ago
On the need for time series data mining benchmarks: a survey and empirical demonstration
In the last decade there has been an explosion of interest in mining time series data. Literally hundreds of papers have introduced new algorithms to index, classify, cluster and s...
Eamonn J. Keogh, Shruti Kasetty
SIGPRO
2011
229views Hardware» more  SIGPRO 2011»
14 years 5 months ago
Fast and exact synthesis of stationary multivariate Gaussian time series using circulant embedding
A fast and exact procedure for the numerical synthesis of stationary multivariate Gaussian time series with a priori prescribed and well controlled autoand cross-covariance functi...
Hannes Helgason, Vladas Pipiras, Patrice Abry
VLDB
2007
ACM
179views Database» more  VLDB 2007»
15 years 10 months ago
Mining Approximate Top-K Subspace Anomalies in Multi-Dimensional Time-Series Data
Market analysis is a representative data analysis process with many applications. In such an analysis, critical numerical measures, such as profit and sales, fluctuate over time a...
Xiaolei Li, Jiawei Han