Finding Time Series Motifs in Disk-Resident Data

  title={Finding Time Series Motifs in Disk-Resident Data},
  author={Abdullah Mueen and Eamonn J. Keogh and Nima Bigdely Shamlo},
  journal={2009 Ninth IEEE International Conference on Data Mining},
Time series motifs are sets of very similar subsequences of a long time series. They are of interest in their own right, and are also used as inputs in several higher-level data mining algorithms including classification, clustering, rule-discovery and summarization. In spite of extensive research in recent years, finding exact time series motifs in massive databases is an open problem. Previous efforts either found approximate motifs or considered relatively small datasets residing in main… CONTINUE READING
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