Streaming Pattern Discovery in Multiple Time-Series

  title={Streaming Pattern Discovery in Multiple Time-Series},
  author={Spiros Papadimitriou and Jimeng Sun and Christos Faloutsos},
In this paper author introduced Streaming Pattern Discovery in Multiple Time-Series (SPIRIT) to discover correlations that efficiently and effectively summarize large collections of streams. The approach incrementally finds the correlations and hidden variables from n numerical data streams at time t .The approach successfully deal with the missing values and the discovered hidden variables can be efficient, resource forecasting. The approach is suggested to answer the common applications like… CONTINUE READING
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tracking of discrete phenomena in sensor network databases

  • A. Arasu, B. Babcock, S. Babu, J. McAlister, J. Widom
  • In SSDBM
  • 2005

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