Exploration of Massive Crime Data Sets through Data Mining Techniques
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Lee, Ickjai
Estivill-Castro, Vladimir
Estivill-Castro, Vladimir
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Date
2011
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Abstract
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.
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Applied Artificial Intelligence
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25
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5
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Cognitive and computational psychology