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» Summarizing Neonatal Time Series Data
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ICDM
2007
IEEE
196views Data Mining» more  ICDM 2007»
14 years 2 days ago
Diagnosing Similarity of Oscillation Trends in Time Series
Sensor networks have increased the amount and variety of temporal data available, requiring the definition of new techniques for data mining. Related research typically addresses...
Leonardo E. Mariote, Claudia Bauzer Medeiros, Rica...
ICDM
2005
IEEE
271views Data Mining» more  ICDM 2005»
13 years 11 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
2003
ACM
118views Data Mining» more  KDD 2003»
14 years 6 months ago
Generating English summaries of time series data using the Gricean maxims
We are developing technology for generating English textual summaries of time-series data, in three domains: weather forecasts, gas-turbine sensor readings, and hospital intensive...
Somayajulu Sripada, Ehud Reiter, Jim Hunter, Jin Y...
SDM
2007
SIAM
171views Data Mining» more  SDM 2007»
13 years 7 months ago
A Better Alternative to Piecewise Linear Time Series Segmentation
Time series are difficult to monitor, summarize and predict. Segmentation organizes time series into few intervals having uniform characteristics (flatness, linearity, modality,...
Daniel Lemire
SDM
2009
SIAM
164views Data Mining» more  SDM 2009»
14 years 2 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...