Journal article
Data mining and crime analysis
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, Vol.1(2), pp.147-153
2011
Abstract
An essential component of criminal investigation involves the interrogation of large databases of information held by police and other criminal justice agencies. Data mining and decision support systems have an important role to play in assisting human inference in this forensic domain that creates one of the most challenging decision-making environments. Technologies range widely and include social network analysis, geographical information systems, and data mining technologies for clustering crimes, finding links between crime and profiling offenders, identifying criminal networks, matching crimes, generating suspects, and predicting criminal activity. This paper does not intend to cover the gamut of techniques available to the investigator of crime as this has been presented elsewhere (Oatley GC, Ewart BW, Zeleznikow J. Decision support systems for police: lessons from the application of data mining techniques to ‘soft’ forensic evidence. Artif Intell Law 2006, 14:35–100). Rather, the objective is to highlight issues of implementation and interpretation of the techniques available to the crime analyst. To this end, the authors draw from their experiences of working with real-world crime databases (Oatley GC, Belem B, Fernandes K, Hoggarth E, Holland B, Lewis C, Meier P, Morgan K, Santhanam J, et al. The gang gun-crime problem—solutions from social network theory, epidemiology, cellular automata, Bayesian networks and spatial statistics. Accepted: book chapter for IEEE publication Computational Forensics; 2008; Oatley GC, McGarry K, Ewart BW. Offender network metrics. WSEAS Trans Inf Sci Appl 2006, 3:2440–2448; Oatley GC, Ewart BW. Crimes analysis software: pins in maps, clustering and Bayes net prediction. Expert Syst Appl 2003, 25:569–588), involving gun and gang crime, fraud, terrorism, burglary, and retail crime.
Details
- Title
- Data mining and crime analysis
- Authors/Creators
- G. Oatley (Author/Creator) - Cardiff Metropolitan UniversityB. Ewart (Author/Creator) - University of Sunderland
- Publication Details
- Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, Vol.1(2), pp.147-153
- Publisher
- Wiley
- Identifiers
- 991005540384507891
- Copyright
- © 2011 John Wiley & Sons, Inc.
- Murdoch Affiliation
- Murdoch University
- Language
- English
- Resource Type
- Journal article
UN Sustainable Development Goals (SDGs)
This output has contributed to the advancement of the following goals:
Source: InCites
Metrics
68 Record Views
InCites Highlights
These are selected metrics from InCites Benchmarking & Analytics tool, related to this output
- Citation topics
- 2 Chemistry
- 2.244 Chemometrics
- 2.244.1784 Forensic Spectroscopy
- Web Of Science research areas
- Computer Science, Artificial Intelligence
- Computer Science, Theory & Methods
- ESI research areas
- Computer Science