Dynamic pattern analysis framework for cooperative crime prevention

Kelvin Leong, Junco Li, Stephen Chan, Vincent To Yee Ng

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)

Abstract

Spatial analysis plays a key role in crime prevention. Traditional approaches such as clustering can find static patterns but do not consider the change of spatial patterns over time. In this paper, we introduce a new analysis framework, Dynamic Pattern Analysis Framework (DPA Framework) focusing on two types of related dynamic patterns: the displacement or diffusion of spatial patterns over time and the similarity between spatial patterns of different periods. The new framework aims to support cooperative crime prevention in a district of Hong Kong.
Original languageEnglish
Title of host publicationProceedings of the 2008 12th International Conference on Computer Supported Cooperative Work in Design, CSCWD
Pages1053-1058
Number of pages6
Volume2
DOIs
Publication statusPublished - 10 Sep 2008
Event2008 12th International Conference on Computer Supported Cooperative Work in Design, CSCWD - Xi'an, China
Duration: 16 Apr 200818 Apr 2008

Conference

Conference2008 12th International Conference on Computer Supported Cooperative Work in Design, CSCWD
Country/TerritoryChina
CityXi'an
Period16/04/0818/04/08

Keywords

  • Cooperative crime prevention
  • Pattern analysis
  • Spatial pattern

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Human-Computer Interaction

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