Similarity Search Over Data Stream using LPC-DTW

Effective similarity search over data stream is of importance for applications like network monitoring, information retrieval and financial service, etc. Linear predictive coding (LPC) is a tool using the information of a linear predictive model. In this paper, we propose similarity search over data stream based on LPC cepstral coefficients using dynamic time warping (DTW). Compared with traditional approaches, such as similarity search based on discrete Fourier transform (DFT) and discrete wavelet transform (DWT), the proposed method LPC-DTW can use fewer coefficients to capture desired features from data stream for similarity search. In distance metric of similarity search, DTW that replaces the Euclidean distance metric could bring better performance. The relative experiment results demonstrate the proposed method is better than the traditional approaches.