An Efficient Range Query Under the Time Warping Distance

Abstract

Time series are comprehensively appeared and developed in many applications. Similarity search under time warping has attracted much interest between the time series in the large databases. DTW (Dynamic Time Warping) is a robust distance measure and is superior to Euclidean distance. Nevertheless, it is more unfortunate that DTW has a quadratic time and the false dismissals are come forth since DTW distance does not satisfy the triangular inequality. In this paper, we propose an efficient range query algorithm based on a new similarity search method under time warping. When our range query applies for this method, it can remove the significant non-qualify time series as early as possible. Hence, it speeds up the calculation time and reduces the number of scanning the time series. Guaranteeing no false dismissals the lower bounding function is advised that consistently underestimate the DTW distance and satisfy the triangular inequality. Through the experimental results, our range query algorithm outperforms the existing others.