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ICDM
2009
IEEE
121views Data Mining» more  ICDM 2009»
15 years 6 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...
TMI
2008
136views more  TMI 2008»
14 years 11 months ago
Classification of fMRI Time Series in a Low-Dimensional Subspace With a Spatial Prior
We propose a new method for detecting activation in functional magnetic resonance imaging (fMRI) data. We project the fMRI time series on a low-dimensional subspace spanned by wave...
François G. Meyer, Xilin Shen
RECOMB
2002
Springer
15 years 12 months ago
A new approach to analyzing gene expression time series data
We present algorithms for time-series gene expression analysis that permit the principled estimation of unobserved timepoints, clustering, and dataset alignment. Each expression p...
Ziv Bar-Joseph, Georg Gerber, David K. Gifford, To...
KDD
2010
ACM
199views Data Mining» more  KDD 2010»
15 years 3 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
TSE
2002
96views more  TSE 2002»
14 years 11 months ago
Better Reliability Assessment and Prediction through Data Clustering
This paper presents a new approach to software reliability modeling by grouping data into clusters of homogeneous failure intensities. This series of data clusters associated with...
Jeff Tian