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» Online discovery and maintenance of time series motifs
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KDD
2010
ACM
199views Data Mining» more  KDD 2010»
13 years 8 months ago
Online discovery and maintenance of time series motifs
The detection of repeated subsequences, time series motifs, is a problem which has been shown to have great utility for several higher-level data mining algorithms, including clas...
Abdullah Mueen, Eamonn J. Keogh
KDD
2003
ACM
146views Data Mining» more  KDD 2003»
14 years 5 months ago
Probabilistic discovery of time series motifs
Several important time series data mining problems reduce to the core task of finding approximately repeated subsequences in a longer time series. In an earlier work, we formalize...
Bill Yuan-chi Chiu, Eamonn J. Keogh, Stefano Lonar...
SDM
2010
SIAM
202views Data Mining» more  SDM 2010»
13 years 2 months ago
Multiresolution Motif Discovery in Time Series
Time series motif discovery is an important problem with applications in a variety of areas that range from telecommunications to medicine. Several algorithms have been proposed t...
Nuno Castro, Paulo J. Azevedo
SDM
2009
SIAM
164views Data Mining» more  SDM 2009»
14 years 1 months ago
Exact Discovery of Time Series Motifs.
Time series motifs are pairs of individual time series, or subsequences of a longer time series, which are very similar to each other. As with their discrete analogues in computat...
Abdullah Mueen, Eamonn J. Keogh, M. Brandon Westov...
ICDM
2003
IEEE
240views Data Mining» more  ICDM 2003»
13 years 9 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