Criminal cross correlation mining and visualization

Phillips, Peter, and Lee, Ickjai (2009) Criminal cross correlation mining and visualization. In: Proceedings of the Pacific-Asia Workshop on Intelligence and Security Informatics 2009, pp. 2-13. From: Pacific-Asia Workshop on Intelligence and Security Informatics 2009, 27 April 2009, Bangkok, Thailand.

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Abstract

Criminals are creatures of habit and their crime activities are geospatially, temporally and thematically correlated. Discovering these correlations is a core component of intelligence-led policing and allows for a deeper insight into the complex nature of criminal behavior. A spatial bivariate correlation measure should be used to discover these patterns from heterogeneous data types. We introduce a bivariate spatial correlation approach for crime analysis that can be extended to extract multivariate cross correlations. It is able to extract the top-k and bottom-k associative features from areal aggregated datasets and visualize the resulting patterns. We demonstrate our approach with real crime datasets and provide a comparison with other techniques. Experimental results reveal the applicability and usefulness of the proposed approach.

Item ID: 8240
Item Type: Conference Item (Refereed Research Paper - E1)
Keywords: crime data mining, correlation mining, spatial data mining, visualization
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ISBN: 978-3-642-01392-8
ISSN: 1611-3349
Date Deposited: 18 Mar 2010 00:28
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%
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