DUST: a generalized notion of similarity between uncertain time series

  title={DUST: a generalized notion of similarity between uncertain time series},
  author={Smruti R. Sarangi and Karin Murthy},
Large-scale sensor deployments and an increased use of privacy-preserving transformations have led to an increasing interest in mining uncertain time series data. Traditional distance measures such as Euclidean distance or dynamic time warping are not always effective for analyzing uncertain time series data. Recently, some measures have been proposed to account for uncertainty in time series data. However, we show in this paper that their applicability is limited. In specific, these approaches… CONTINUE READING
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The ucr time series classification/clustering homepage. www.cs.ucr.edu/~eamonn/time_series_data

  • E. Keogh, X. Xi, L. Wei, C. A. Ratanamahatana
  • Accessed on Feb
  • 2010
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