An improvement of symbolic aggregate approximation distance measure for time series

@article{Sun2014AnIO,
  title={An improvement of symbolic aggregate approximation distance measure for time series},
  author={Youqiang Sun and Jiuyong Li and Jixue Liu and Bing-Yu Sun and Christopher Chow},
  journal={Neurocomputing},
  year={2014},
  volume={138},
  pages={189-198}
}
Symbolic Aggregate approXimation (SAX) as a major symbolic representation has been widely used in many time series data mining applications. However, because a symbol is mapped from the average value of a segment, the SAX ignores important information in a segment, namely the trend of the value change in the segment. Such a miss may cause a wrong classification in some cases, since the SAX representation cannot distinguish different time series with similar average values but different trends… CONTINUE READING

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