Abstract
Because of the appropriate algorithm of measuring multiple granularities time-series is few, this article advanced a similarity matching algorithm for multiple granularities time-series, which based on the ideal of time calibrator and hypothesis test. It firstly expounded the definition of multiple granularities time-series, and proposed a sample of distance; secondly, it put forward the similarity matching algorithm of multiple granularities time-series; finally, the experimental result proved that the algorithm can effectively reflect the time-series of multiple granularities.
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Hao, W., Zhao, E., Zhang, H., Chen, G., Jin, D. (2010). Research on Similarity Matching for Multiple Granularities Time-Series Data. In: Cao, L., Feng, Y., Zhong, J. (eds) Advanced Data Mining and Applications. ADMA 2010. Lecture Notes in Computer Science(), vol 6440. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17316-5_52
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DOI: https://doi.org/10.1007/978-3-642-17316-5_52
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-17315-8
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