Group Behaviour Analysis of London Foot Patrol Police

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