Exploration of Massive Crime Data Sets through Data Mining Techniques

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Title Exploration of Massive Crime Data Sets through Data Mining Techniques
Author Lee, Ickjai; Estivill-Castro, Vladimir
Journal Name Applied Artificial Intelligence
Year Published 2011
Place of publication United States
Publisher Taylor & Francis Inc.
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.
Peer Reviewed Yes
Published Yes
Alternative URI http://dx.doi.org/10.1080/08839514.2011.570153
Volume 25
Issue Number 5
Page from 362
Page to 379
ISSN 0883-9514
Date Accessioned 2011-12-08; 2012-02-13T05:04:38Z
Research Centre Institute for Integrated and Intelligent Systems
Faculty Faculty of Science, Environment, Engineering and Technology
Subject Pattern Recognition and Data Mining
URI http://hdl.handle.net/10072/42460
Publication Type Journal Articles (Refereed Article)
Publication Type Code c1

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