Similarity Search in Multidimensional Time Series using the Coulomb’s Law - Ribeiro, Marcela Xavier; Andrade, Claudinei Garcia de (Journal of Information and Data Management, 2014)
With the technological advancement, associated to the low production cost of instruments used to collect observations, there has been an increase in the amount of available data for analysis. The collected data present intrinsic relations between them that are not perceptive without a careful analysis, requiring the use of specic techniques to manipulate them. In this context, we propose a time series descriptor, based on the principle of the Coulomb Law, to perform similarity search over multidimensional time series. The proposed descriptor is composed of a new time series extractor and a new distance function for multidimensional time series. Moreover, this paper presents the Coulomb method that describe how to employ the proposed descriptor to perform similarity search over multidimensional time series. According to the experiments performed over climatic and medical databases, the proposed method promotes a larger reduction in the feature vector size and achieves higher accuracy values when compared with other time series descriptors based on Fourier Transform and Brute-force solution.