Spatiotemporal Data Mining: A Survey
Databases
2022-06-28 v1 Computer Vision and Pattern Recognition
Distributed, Parallel, and Cluster Computing
Machine Learning
Abstract
Spatiotemporal data mining aims to discover interesting, useful but non-trivial patterns in big spatial and spatiotemporal data. They are used in various application domains such as public safety, ecology, epidemiology, earth science, etc. This problem is challenging because of the high societal cost of spurious patterns and exorbitant computational cost. Recent surveys of spatiotemporal data mining need update due to rapid growth. In addition, they did not adequately survey parallel techniques for spatiotemporal data mining. This paper provides a more up-to-date survey of spatiotemporal data mining methods. Furthermore, it has a detailed survey of parallel formulations of spatiotemporal data mining.
Cite
@article{arxiv.2206.12753,
title = {Spatiotemporal Data Mining: A Survey},
author = {Arun Sharma and Zhe Jiang and Shashi Shekhar},
journal= {arXiv preprint arXiv:2206.12753},
year = {2022}
}