Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/31849
Title: An application of cyclic signature (CS) clustering for spatial-temporal pattern analysis to support public safety work
Authors: Chan, SCF 
Leong, K
Keywords: Data mining
Clustering
Public safety work
Spatial-temporal pattern analysis
Issue Date: 2010
Publisher: IEEE
Source: 2010 IEEE International Conference on Systems Man and Cybernetics (SMC), 10-13 October 2010, Istanbul, p. 2716-2723 How to cite?
Abstract: In this paper, we propose a novel approach, Cyclic Signature (CS) clustering, to analyze spatial-temporal pattern. CS clustering is based on the calendar regularities of events to analyze spatial-temporal patterns. An experiment, based on a set of reported crime data for a district in Hong Kong, was performed to compare CS clustering against traditional clustering approaches. The results show that CS clustering can provide information which differs greatly from traditional clustering approaches. In addition, the groups created by CS clustering have higher intra-cluster similarities and lower inter-cluster similarities than traditional clustering approaches.
URI: http://hdl.handle.net/10397/31849
ISBN: 978-1-4244-6586-6
ISSN: 1062-922X
DOI: 10.1109/ICSMC.2010.5641797
Appears in Collections:Conference Paper

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