Abstract
Based on definitions of 1st and 2nd order atomic pattern of time series, this paper deduces n-th order atomic pattern, where partially-ordered relationship within these patterns is discussed. The framework enables more refined comparison between sequences, based on which we propose Template-Based Matching Algorithm. The experimental result has verified its distinct advantages over some similar and classical approaches both in accuracy and performance.
Index Terms: time series, pattern recognition, case-based reasoning, partially order, lattice.
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Tang, Y. (2006). Partially Ordered Template-Based Matching Algorithm for Financial Time Series. In: Ali, M., Dapoigny, R. (eds) Advances in Applied Artificial Intelligence. IEA/AIE 2006. Lecture Notes in Computer Science(), vol 4031. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11779568_113
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DOI: https://doi.org/10.1007/11779568_113
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