Multivarite areal aggregated crime analysis through cross correlation

Phillips, Peter, and Lee, Ickjai (2009) Multivarite areal aggregated crime analysis through cross correlation. In: Proceedings of the 2008 Second International Symposium on Intelligent Information Technology Application (IITA) (2), pp. 295-298. From: 2008 Second International Symposium on Intelligent Information Technology Application (IITA) , 21-22 December 2008, Shanghai, China.

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Abstract

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.

Item ID: 7919
Item Type: Conference Item (Refereed Research Paper - E1)
Keywords: correlation analysis, geospatial data mining, crime analysis
ISBN: 978-0-7695-3563-0
Date Deposited: 15 Jan 2010 01:41
FoR Codes: 08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080109 Pattern Recognition and Data Mining @ 50%
09 ENGINEERING > 0909 Geomatic Engineering > 090903 Geospatial Information Systems @ 50%
SEO Codes: 89 INFORMATION AND COMMUNICATION SERVICES > 8902 Computer Software and Services > 890205 Information Processing Services (incl. Data Entry and Capture) @ 100%
Citation Count from Web of Science Web of Science 2
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