Motif-based Classification using Enhanced Sub-Sequence-Based Dynamic Time Warping

Mohammed Alshehri, Mohammed Alshehri, Frans Coenen, Keith Dures

2021

Abstract

In time series analysis, Dynamic Time Warping (DTW) coupled with k Nearest Neighbour classification, where k = 1, is the most commonly used classification model. Even though DTW has a quadratic complexity, it outperforms other similarity measurements in terms of accuracy, hence its popularity. This paper presents two motif-based mechanisms directed at speeding up the DTW process in such a way that accuracy is not adversely affected: (i) the Differential Sub-Sequence Motifs (DSSM) mechanism and (ii) the Matrix Profile Sub-Sequence Motifs (MPSSM) mechanism. Both mechanisms are fully described and evaluated. The evaluation indicates that both DSSM and MPSSM can speed up the DTW process while producing a better, or at least comparable accuracy, in 90% of cases.

Paper Citation

in Harvard Style

Alshehri M., Coenen F. and Dures K. (2021). Motif-based Classification using Enhanced Sub-Sequence-Based Dynamic Time Warping. In Proceedings of the 10th International Conference on Data Science, Technology and Applications - Volume 1: DATA, ISBN 978-989-758-521-0, pages 184-191. DOI: 10.5220/0010519301840191

in Bibtex Style

@conference{data21,
author={Mohammed Alshehri and Frans Coenen and Keith Dures},
title={Motif-based Classification using Enhanced Sub-Sequence-Based Dynamic Time Warping},
booktitle={Proceedings of the 10th International Conference on Data Science, Technology and Applications - Volume 1: DATA,},
year={2021},
pages={184-191},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010519301840191},
isbn={978-989-758-521-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 10th International Conference on Data Science, Technology and Applications - Volume 1: DATA,
TI - Motif-based Classification using Enhanced Sub-Sequence-Based Dynamic Time Warping
SN - 978-989-758-521-0
AU - Alshehri M.
AU - Coenen F.
AU - Dures K.
PY - 2021
SP - 184
EP - 191
DO - 10.5220/0010519301840191