Real Time Detection and Tracking of Spatial Event Clusters
Abstract
We demonstrate a system of tools for real-time detection of significant clusters of spatial events and observing their evolution. The tools include an incremental stream clustering algorithm, interactive techniques for controlling its operation, a dynamic map display showing the current situation, and displays for investigating the cluster evolution (time line and space-time cube).
Cite
Text
Andrienko et al. "Real Time Detection and Tracking of Spatial Event Clusters." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2015. doi:10.1007/978-3-319-23461-8_38Markdown
[Andrienko et al. "Real Time Detection and Tracking of Spatial Event Clusters." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2015.](https://mlanthology.org/ecmlpkdd/2015/andrienko2015ecmlpkdd-real/) doi:10.1007/978-3-319-23461-8_38BibTeX
@inproceedings{andrienko2015ecmlpkdd-real,
title = {{Real Time Detection and Tracking of Spatial Event Clusters}},
author = {Andrienko, Natalia V. and Andrienko, Gennady L. and Fuchs, Georg and Rinzivillo, Salvatore and Betz, Hans-Dieter},
booktitle = {European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
year = {2015},
pages = {316-319},
doi = {10.1007/978-3-319-23461-8_38},
url = {https://mlanthology.org/ecmlpkdd/2015/andrienko2015ecmlpkdd-real/}
}