Sub-Sequence-Based Dynamic Time Warping

Mohammed Alshehri, Frans Coenen, Keith Dures

2019

Abstract

In time series classification the most commonly used approach is k Nearest Neighbor classification, where k = 1, coupled with Dynamic Time Warping (DTW) similarity checking. A challenge is that the DTW process is computationally expensive. This paper presents a new approach for speeding-up the DTW process, Sub-Sequence-Based DTW, which offers the additional benefit of improving accuracy. This paper also presents an analysis of the impact of the Sub-Sequence-Based method in terms of efficiency and effectiveness in comparison with standard DTW and the Sakoe-Chiba Band technique.

Paper Citation

in Harvard Style

Alshehri M., Coenen F. and Dures K. (2019). Sub-Sequence-Based Dynamic Time Warping. In Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - Volume 1: KDIR; ISBN 978-989-758-382-7, SciTePress, pages 274-281. DOI: 10.5220/0008053402740281

in Bibtex Style

@conference{kdir19,
author={Mohammed Alshehri and Frans Coenen and Keith Dures},
title={Sub-Sequence-Based Dynamic Time Warping},
booktitle={Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - Volume 1: KDIR},
year={2019},
pages={274-281},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008053402740281},
isbn={978-989-758-382-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - Volume 1: KDIR
TI - Sub-Sequence-Based Dynamic Time Warping
SN - 978-989-758-382-7
AU - Alshehri M.
AU - Coenen F.
AU - Dures K.
PY - 2019
SP - 274
EP - 281
DO - 10.5220/0008053402740281
PB - SciTePress