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UAL Research Online

A review of data mining applications in crime

Hassani, H. and Huang, X. and Silva, E.S. and Ghodsi, M. (2016) A review of data mining applications in crime. Statistical Analysis and Data Mining: The ASA Data Science Journal, 9 (3). pp. 139-154. ISSN 1932-1872

Type of Research: Article
Creators: Hassani, H. and Huang, X. and Silva, E.S. and Ghodsi, M.

Crime continues to remain a severe threat to all communities and nations across the globe alongside the sophistication in technology and processes that are being exploited to enable highly complex criminal activities. Data mining, the process of uncovering hidden information from Big Data, is now an important tool for investigating, curbing and preventing crime and is exploited by both private and government institutions around the world. The primary aim of this paper is to provide a concise review of the data mining applications in crime. To this end, the paper reviews over 100 applications of data mining in crime, covering a substantial quantity of research to date, presented in chronological order with an overview table of many important data mining applications in the crime domain as a reference directory. The data mining techniques themselves are briefly introduced to the reader and these include entity extraction, clustering, association rule mining, decision trees, support vector machines, naive Bayes rule, neural networks and social network analysis amongst others.

Official Website: http://onlinelibrary.wiley.com/doi/10.1002/sam.11312/full
Additional Information (Publicly available):

The text of this article is restricted due to copyright issues. Please contact UAL Research Online to request a copy.

Keywords/subjects not otherwise listed: Crime, Data Mining, Review
Your affiliations with UAL: Colleges > London College of Fashion
Date: June 2016
Digital Object Identifier: 10.1002/sam.11312
Date Deposited: 28 Jun 2016 11:38
Last Modified: 28 Apr 2017 06:25
Item ID: 9554
URI: https://ualresearchonline.arts.ac.uk/id/eprint/9554

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