Combining SAX and Piecewise Linear Approximation to Improve Similarity Search on Financial Time Series
Information Technology Convergence 2007 ISITC 2007 International Symposium on (2007)
- ISBN: 0769530451
- DOI: 10.1109/ISITC.2007.24
Available from ieeexplore.ieee.org
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Abstract
Efficient and accurate similarity searching on a large time series data set is an important but non- trivial problem. In this work, we propose a new approach to improve the quality of similarity search on time series data by combining symbolic aggregate approximation (SAX) and piecewise linear approximation. The approach consists of three steps: transforming real valued time series sequences to symbolic strings via SAX, pattern matching on the symbolic strings and a post-processing via Piecewise Linear Approximation.
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Combining SAX and Piecewise Linear Approximation to Improve Similarity Search on Financial Time Series
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