Extended SAX : Extension of Symbolic Aggregate Approximation for Financial Time Series Data Representation

  title={Extended SAX : Extension of Symbolic Aggregate Approximation for Financial Time Series Data Representation},
  author={Battuguldur Lkhagva and Yu Suzuki},
Efficient and accurate similarity searching for a large amount of time series data set is an important but non-trivial problem. Many dimensionality reduction techniques have been proposed for effective representation of time series data in order to realize such similarity searching, including Singular Value Decomposition (SVD), the Discrete Fourier transform (DFT), the Adaptive Piecewise Constant Approximation (APCA), and the recently proposed Symbolic Aggregate Approximation (SAX). In this… CONTINUE READING
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