Abstract
We present a method for visual search in multidimensional time series based on Coulomb’s law. The proposed method integrates: a descriptor based on Coulomb’s law for dimensionality reduction in time series; a system to perform similarity searching in time series; and, a module for the visualization of results. Experiments were performed using real data, indicating that the proposed method broadens the quality of through similarity queries in time series.
We would like to thank FAPESP, CAPES and CNPq for the financial support.
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de Andrade, C.G., Ribeiro, M.X. (2014). A Similarity-Based Method for Visual Search in Time Series Using Coulomb’s Law. In: Traina, A.J.M., Traina, C., Cordeiro, R.L.F. (eds) Similarity Search and Applications. SISAP 2014. Lecture Notes in Computer Science, vol 8821. Springer, Cham. https://doi.org/10.1007/978-3-319-11988-5_22
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DOI: https://doi.org/10.1007/978-3-319-11988-5_22
Publisher Name: Springer, Cham
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