A new approach for optimal time-series segmentation

Abstract

This paper proposes a new optimal approach, called OSTS, to improve the segmentation of time series. The proposed method is based on A* algorithm and it uses an improved version of the well-known Salotti method for obtaining optimal polygonal approximations. Firstly, a suboptimal method for time-series segmentation is applied to obtain pruning values. In this case, a suboptimal method based on Bottom-Up technique is selected. Then, the results of the suboptimal method are used as pruning values to reduce the computational time of the proposed method. The proposal has been compared to other suboptimal methods and the results have shown that the method is optimal, and, in some cases, the computational time is similar to other suboptimal methods.