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

Open access link

DOI

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

Citation

BibTeX

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