Atomic wedgie: Efficient query filtering for streaming time series

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Atomic wedgie: Efficient query filtering for streaming time series (2005)

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by Li Wei , Eamonn Keogh , Helga Van , Herle Agenor Mafra-neto

Venue:	In Proceedings of the 5 th IEEE International Conference on Data Mining (ICDM 2005
Citations:	23 - 6 self

BibTeX

@INPROCEEDINGS{Wei05atomicwedgie:,
    author = {Li Wei and Eamonn Keogh and Helga Van and Herle Agenor Mafra-neto},
    title = {Atomic wedgie: Efficient query filtering for streaming time series},
    booktitle = {In Proceedings of the 5 th IEEE International Conference on Data Mining (ICDM 2005},
    year = {2005},
    pages = {490--497}
}

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Abstract

In many applications it is desirable to monitor a streaming time series for predefined patterns. In domains as diverse as the monitoring of space telemetry, patient intensive care data, and insect populations, where data streams at a high rate and the number of predefined patterns is large, it may be impossible for the comparison algorithm to keep up. We propose a novel technique that exploits the commonality among the predefined patterns to allow monitoring at higher bandwidths, while maintaining a guarantee of no false dismissals. Our approach is based on the widely used envelope-based lower bounding technique. Extensive experiments demonstrate that our approach achieves tremendous improvements in performance in the offline case, and significant improvements in the fastest possible arrival rate of the data stream that can be processed with guaranteed no false dismissal. 1.

Keyphrases

atomic wedgie time series efficient query filtering predefined pattern data stream false dismissal bounding technique insect population patient intensive care data many application tremendous improvement space telemetry possible arrival rate high rate significant improvement novel technique comparison algorithm offline case streaming time series extensive experiment

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