Mining Sequence Data & Time Series Data
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Mining Sequence Data & Time Series Data
Abstract—Mining Sequence Data & Time Series Data. 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, < Final Year Projects > 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.
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