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.
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