Deep Time-Series Clustering: A Review

Ali Alqahtani, Mohammed Ali, Xianghua Xie and Mark W Jones

Abstract

We present a comprehensive, detailed review of time-series data analysis, with emphasis on deep time-series clustering (DTSC), and a case study in the context of movement behavior clustering utilizing the deep clustering method. Specifically, we modified the DCAE architectures to suit time-series data at the time of our prior deep clustering work. Lately, several works have been carried out on deep clustering of time-series data. We also review these works and identify state-of-the-art, as well as present an outlook on this important field of DTSC from five important perspectives.

Related Files

PDF iconOpen access link

DOI

10.3390/electronics10233001
https://dx.doi.org/10.3390/electronics10233001

Citation

Ali Alqahtani, Mohammed Ali, Xianghua Xie and Mark W Jones, Deep Time-Series Clustering: A Review, Electronics 10(23):3001 (2021). https://dx.doi.org/10.3390/electronics10233001

BibTeX

@article{TimeSeriesClustering,
title = {Deep Time-Series Clustering: A Review},
author = {Ali Alqahtani and Mohammed Ali and Xianghua Xie and Mark W Jones},
journal = {Electronics},
volume = {10},
number = {23},
pages = {3001},
date = {2021-12-02},
year = {2021},
month = {12},
day = {2},
issn = {2079-9292},
doi = {10.3390/electronics10233001},
}