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...
The past decade has seen a wealth of research on time series representations, because the manipulation, storage, and indexing of large volumes of raw time series data is impractic...
Themistoklis Palpanas, Michail Vlachos, Eamonn J. ...
Managing large-scale time series databases has attracted significant attention in the database community recently. Related fundamental problems such as dimensionality reduction, tr...
A fast online algorithm was developed for polygonal approximation of signals and curves with a minimum number of line segments for a given constraint on the standard deviation of ...
The past decade has seen a wealth of research on time series representations, because the manipulation, storage, and indexing of large volumes of raw time series data is impractica...
Themis Palpanas, Michail Vlachos, Eamonn J. Keogh,...