caa a22 4500 445331747 CHVBK 20180317142739.0 cr unu---uuuuu 170323e20110101xx s 000 0 eng 10.1007/s10707-010-0116-1 doi (NATIONALLICENCE)springer-10.1007/s10707-010-0116-1 Crime analysis through spatial areal aggregated density patterns [Elektronische Daten] [Peter Phillips, Ickjai Lee] Intelligent crime analysis allows for a greater understanding of the dynamics of unlawful activities, providing possible answers to where, when and why certain crimes are likely to happen. We propose to model density change among spatial regions using a density tracing based approach that enables reasoning about large areal aggregated crime datasets. We discover patterns among datasets by finding those crime and spatial features that exhibit similar spatial distributions by measuring the dissimilarity of their density traces. The proposed system incorporates both localized clusters (through the use of context sensitive weighting and clustering) and the global distribution trend. Experimental results validate and demonstrate the robustness of our approach. Springer Science+Business Media, LLC, 2010 Crime analysis nationallicence Spatial distribution nationallicence Density tracing nationallicence Areal aggregated data nationallicence Phillips Peter School of Business, Discipline of IT, James Cook University, Townsville, Australia aut Lee Ickjai School of Business, Discipline of IT, James Cook University, Townsville, Australia aut GeoInformatica Springer US; http://www.springer-ny.com 15/1(2011-01-01), 49-74 1384-6175 15:1<49 2011 15 10707 https://doi.org/10.1007/s10707-010-0116-1 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s10707-010-0116-1 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Phillips Peter School of Business, Discipline of IT, James Cook University, Townsville, Australia aut NATIONALLICENCE 700 1- Lee Ickjai School of Business, Discipline of IT, James Cook University, Townsville, Australia aut NATIONALLICENCE 773 0- GeoInformatica Springer US; http://www.springer-ny.com 15/1(2011-01-01), 49-74 1384-6175 15:1<49 2011 15 10707 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer