Crime analysis through spatial areal aggregated density patterns
Phillips, Peter, and Lee, Ickjai (2011) Crime analysis through spatial areal aggregated density patterns. Geoinformatica, 15 (1). pp. 49-74.
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Intelligent crime analysis allows for a greater understanding of the dynamics of unlawful activities, providing possible answers to where, when and why certain crimes are likely to happen. We propose to model density change among spatial regions using a density tracing based approach that enables reasoning about large areal aggregated crime datasets. We discover patterns among datasets by finding those crime and spatial features that exhibit similar spatial distributions by measuring the dissimilarity of their density traces. The proposed system incorporates both localized clusters (through the use of context sensitive weighting and clustering) and the global distribution trend. Experimental results validate and demonstrate the robustness of our approach.
|Item Type:||Article (Refereed Research - C1)|
|FoR Codes:||08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080109 Pattern Recognition and Data Mining @ 100%|
|SEO Codes:||89 INFORMATION AND COMMUNICATION SERVICES > 8902 Computer Software and Services > 890202 Application Tools and System Utilities @ 100%|
|Deposited On:||27 Feb 2012 12:27|
|Last Modified:||19 May 2013 01:42|
Last 12 Months: 0
|Citation Counts with External Providers:||Web of Science: 1|
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