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Detecting and tracking dynamic clusters of spatial events

Andrienko, N., Andrienko, G., Fuchs, G. and Stange, H. (2014). Detecting and tracking dynamic clusters of spatial events. 2014 IEEE Conference on Visual Analytics Science and Technology (VAST), pp. 219-220. doi: 10.1109/VAST.2014.7042499

Abstract

We present a work in progress on developing a tool supporting real-time detection of significant clusters of spatial events and observing their evolution. The tool consists of an incremental stream clustering algorithm and coordinated map and timeline displays showing current situation and cluster evolution.

Publication Type: Article
Additional Information: c) 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
Publisher Keywords: Clustering algorithms; Joining processes; Monitoring; Observers; Real-time systems; Shape; Vehicles
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments: School of Mathematics, Computer Science & Engineering > Computer Science
URI: http://openaccess.city.ac.uk/id/eprint/11978
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