Exploration of massive crime data sets through data mining techniques
Lee, Ickjai, and Estivill-Castro, Vladimir (2011) Exploration of massive crime data sets through data mining techniques. Applied Artificial Intelligence, 25 (5). pp. 362-379.
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We incorporate two data mining techniques, clustering and association-rule mining, into a fruitful exploratory tool for the discovery of spatio-temporal patterns in data-rich environments. This tool is an autonomous pattern detector that efficiently and effectively reveals plausible cause–effect associations among many geographical layers. We present two methods for exploratory analysis and detail algorithms to explore massive databases. We illustrate the algorithms with real crime data sets.
|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 12:34|
|Last Modified:||24 May 2013 01:43|
Last 12 Months: 0
|Citation Counts with External Providers:||Web of Science: 0|
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