Deep Time-Series Clustering: A Review

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.

Automated summary

The article presents a detailed review of time-series data analysis, focusing on deep time-series clustering (DTSC) and a case study in movement behavior clustering using the deep clustering method. It discusses modifications made to DCAE architectures for time-series data and reviews recent works on deep clustering of time-series data. The article also identifies state-of-the-art developments in this field and offers an outlook on DTSC from five important perspectives.