期刊
EXPERT SYSTEMS WITH APPLICATIONS
卷 39, 期 14, 页码 11556-11563出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2012.03.071
关键词
Co-distribution; Areal aggregated data; Crime data mining; Correlation
Crime activities are geospatial phenomena and as such are geospatially, thematically and temporally correlated. We analyze crime datasets in conjunction with socio-economic and socio-demographic factors to discover co-distribution patterns that may contribute to the formulation of crime. We propose a graph based dataset representation that allows us to extract patterns from heterogeneous areal aggregated datasets and visualize the resulting patterns efficiently. We demonstrate our approach with real crime datasets and provide a comparison with other techniques. (C) 2012 Elsevier Ltd. All rights reserved.
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