Sparsification of the Alignment Path Search Space in Dynamic Time Warping

TL;DR

This paper introduces sparsified alignment path search spaces for Dynamic Time Warping, significantly reducing computational costs while maintaining accuracy, through new measures SP-DTW and SP-K rdtw, validated on various datasets.

Contribution

It proposes novel sparsification techniques for DTW, creating two new measures that improve efficiency without sacrificing accuracy compared to traditional methods.

Findings

Significant speed-up in DTW computations.

Maintained classification accuracy with sparsified measures.

Outperformed Sakoe-Chiba approach in accuracy with comparable speed.

Abstract

Temporal data are naturally everywhere, especially in the digital era that sees the advent of big data and internet of things. One major challenge that arises during temporal data analysis and mining is the comparison of time series or sequences, which requires to determine a proper distance or (dis)similarity measure. In this context, the Dynamic Time Warping (DTW) has enjoyed success in many domains, due to its 'temporal elasticity', a property particularly useful when matching temporal data. Unfortunately this dissimilarity measure suffers from a quadratic computational cost, which prohibits its use for large scale applications. This work addresses the sparsification of the alignment path search space for DTW-like measures, essentially to lower their computational cost without loosing on the quality of the measure. As a result of our sparsification approach, two new (dis)similarity measures, namely SP-DTW (Sparsified-Paths search space DTW) and its kernelization SP-K rdtw (Sparsified-Paths search space K rdtw kernel) are proposed for time series comparison. A wide range of public datasets is used to evaluate the efficiency (estimated in term of speed-up ratio and classification accuracy) of the proposed (dis)similarity measures on the 1-Nearest Neighbor (1-NN) and the Support Vector Machine (SVM) classification algorithms. Our experiment shows that our proposed measures provide a significant speed-up without loosing on accuracy. Furthermore, at the cost of a slight reduction of the speedup they significantly outperform on the accuracy criteria the old but well known Sakoe-Chiba approach that reduces the DTW path search space using a symmetric corridor.