Criminal cross correlation mining and visualization
Phillips, Peter, and Lee, Ickjai (2009) Criminal cross correlation mining and visualization. Proceedings of the Pacific-Asia Workshop on Intelligence and Security Informatics 2009. Pacific-Asia Workshop on Intelligence and Security Informatics 2009 , 27 April 2009, Bangkok, Thailand , pp. 2-13.
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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 Type:||Conference Item (Refereed Research Paper - E1)|
|Keywords:||crime data mining, correlation mining, spatial data mining, visualization|
|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%|
|Deposited On:||18 Mar 2010 10:28|
|Last Modified:||16 May 2013 01:03|
Last 12 Months: 0
|Citation Counts with External Providers:||Web of Science: 0|
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