Abstract
We study the problem of segmenting time series stream. Existing segmenting methods for time series mainly focus on the static data, and may be infeasible under the circumstance of time series stream. We propose an approximate method of APCAS(Adaptive Piecewise Constant Approximate Segmentation) to adaptively segment time series stream, which works in linear time. Extensive experiments, both on synthetic and real datasets, show that our approach is efficient and effective.
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Junkui, L., Yuanzhen, W. (2007). APCAS: An Approximate Approach to Adaptively Segment Time Series Stream. In: Dong, G., Lin, X., Wang, W., Yang, Y., Yu, J.X. (eds) Advances in Data and Web Management. APWeb WAIM 2007 2007. Lecture Notes in Computer Science, vol 4505. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72524-4_57
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DOI: https://doi.org/10.1007/978-3-540-72524-4_57
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72483-4
Online ISBN: 978-3-540-72524-4
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