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- W2247359466 abstract "Similarity search for patterns over streaming time series is a big challenge in data mining at present. In the paper, we introduce an efficient method, which performs similarity search for numerous patterns in multiple time-series streams at high-speed rates under the Euclidean distance. The search method matches approximately new-coming time-series sub sequences of time-series streams with given patterns using an overlapped segmentation of time-series data. Moreover, this method is designed for range search not only with the same search radius for all time-series patterns but also the own search radius for each time-series pattern. The experimental results reveal that the search method has the same accuracy as similarity search in static time series, and low wall-clock times." @default.
- W2247359466 created "2016-06-24" @default.
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- W2247359466 date "2015-10-01" @default.
- W2247359466 modified "2023-09-27" @default.
- W2247359466 title "Similarity Search for Numerous Patterns in Multiple High-Speed Time-Series Streams" @default.
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- W2247359466 doi "https://doi.org/10.1109/kse.2015.30" @default.
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