iSAX 2.0: Indexing and Mining One Billion Time Series

  title={iSAX 2.0: Indexing and Mining One Billion Time Series},
  author={Alessandro Camerra and Themis Palpanas and Jin Shieh and Eamonn J. Keogh},
  journal={2010 IEEE International Conference on Data Mining},
There is an increasingly pressing need, by several applications in diverse domains, for developing techniques able to index and mine very large collections of time series. Examples of such applications come from astronomy, biology, the web, and other domains. It is not unusual for these applications to involve numbers of time series in the order of hundreds of millions to billions. However, all relevant techniques that have been proposed in the literature so far have not considered any data… CONTINUE READING
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