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Exploring the Homogeneity of Offenders in Crime Hotspots

Cheng, T; Chen, T; Zhang, Y; (2019) Exploring the Homogeneity of Offenders in Crime Hotspots. In: Geographical Information Science Research- UK (GISRUK) 2019 Proceedings. GISRUK: Newcastle, UK. Green open access

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Abstract

Exploring the homogeneity of offenders within crime hotspots is helpful for not only understanding how the similar offenders commit the crime following the same spatio-temporal pattern, but also for crime prevention or crime investigation work. In this study, we utilise ST-DBSCAN algorithm to detect crime hotspots using historical theft records in central area of Beijing, China. Leveraging demographic information of the associated offenders, we propose three novel entropy-based indices to measure the similarity of offenders. Results show that the crimes concentrated in a narrow space and time span are usually committed by a group of offenders with similar demographics, which is referred to as homogeneous offenders.

Type: Proceedings paper
Title: Exploring the Homogeneity of Offenders in Crime Hotspots
Event: Geographical Information Science Research- UK (GISRUK) 2019
Open access status: An open access version is available from UCL Discovery
Publisher version: http://newcastle.gisruk.org/proceedings/
Language: English
Additional information: This version is the version of record. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Spatial-temporal clustering, homogenous offenders, ST-DBSCAN, entropy, unsupervised learning
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Civil, Environ and Geomatic Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10085142
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