Multivariate areal aggregated crime analysis through cross correlation
Conference Publication ResearchOnline@JCUAbstract
Intelligent crime analysis allows for a greater understanding of the dynamics of unlawful activities. Discovering crime and spatial features that exhibit strong correlation allows a deeper insight into the complex question of crime analysis. To effectively search heterogeneous data types for cross correlation, a spatial multivariate association measure can be used. We demonstrate a bivariate spatial association approach for crime analysis that can be extended to extract multivarite cross correlation. It is able to extract the top-k and bottom-k associative features from areal aggregated datasets. Experimental results demonstrate our approach using real crime datasets.
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Publication Name
2008 International Workshop on Geoscience and Remote Sensing
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ISBN/ISSN
978-0-7695-3505-0
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Pages Count
4
Location
Shanghai, China
Publisher
IEEE Computer Society
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Publisher Location
Los Alamitos, Calif.
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Date
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EISSN
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DOI
10.1109/ETTandGRS.2008.210