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).
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© 2015 Springer International Publishing Switzerland
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Andrienko, N., Andrienko, G., Fuchs, G., Rinzivillo, S., Betz, HD. (2015). Real Time Detection and Tracking of Spatial Event Clusters. In: Bifet, A., et al. Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2015. Lecture Notes in Computer Science(), vol 9286. Springer, Cham. https://doi.org/10.1007/978-3-319-23461-8_38
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DOI: https://doi.org/10.1007/978-3-319-23461-8_38
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Online ISBN: 978-3-319-23461-8
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