Shen, J;
Cheng, T;
(2015)
Group Behaviour Analysis of London Foot Patrol Police.
In:
GIS Research UK 2015 (GISRUK2015) Proceedings.
(pp. pp. 565-569).
University of Leeds: Leeds.
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Abstract
The main objective of this research is to propose a method for group movement pattern generalisation and classification. To this end, DBSCAN is used on stay points for POI identification. Then, movement features are extracted and selected for the behaviour classification. A kernel-based Support Vector Machine method is developed to infer the working types of the officers based on the selected features depicting their movement histories. By analysing the geo-tagged police data, we demonstrate how this method can be used to reveal user information, especially interest information based on their POIs and spatial-temporal movement patterns
Type: | Proceedings paper |
---|---|
Title: | Group Behaviour Analysis of London Foot Patrol Police |
Event: | GIS Research UK 2015 (GISRUK2015) |
Location: | Leeds, UK |
Dates: | 15 April 2015 - 17 April 2015 |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.6084/m9.figshare.1491375.v3 |
Publisher version: | https://doi.org/10.6084/m9.figshare.1491375.v3 |
Language: | English |
Additional information: | This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license. |
Keywords: | Policing, Travel Pattern, Machine Learning, SVM Classification, POI |
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 UCL > Provost and Vice Provost Offices > UCL SLASH UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of Arts and Humanities UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of Arts and Humanities > European and Intl Social and Political Studs |
URI: | https://discovery.ucl.ac.uk/id/eprint/1529544 |
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