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.
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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 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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