Crime data mining: A general framework and some examples

Hsinchun Chen; Wingyan Chung; Jennifer Jie Xu; Gang Wang; Yi Qin; Michael Chau

doi:10.1109/MC.2004.1297301

Crime data mining: A general framework and some examples

Hsinchun Chen, Wingyan Chung, Jennifer Jie Xu, Gang Wang, Yi Qin, Michael Chau

Research output: Contribution to specialist publication › Article

386 Scopus citations

Abstract

A general framework for crime data mining that draws on experience gained with the Coplink project at the University of Arizona is presented. By increasing efficiency and reducing errors, this scheme facilitates police work and enables investigators to allocate their time to other valuable tasks.

Original language	English (US)
Pages	50-56
Number of pages	7
Volume	37
No	4
Specialist publication	Computer
DOIs	https://doi.org/10.1109/MC.2004.1297301
State	Published - Apr 2004

ASJC Scopus subject areas

General Computer Science

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10.1109/MC.2004.1297301

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title = "Crime data mining: A general framework and some examples",

abstract = "A general framework for crime data mining that draws on experience gained with the Coplink project at the University of Arizona is presented. By increasing efficiency and reducing errors, this scheme facilitates police work and enables investigators to allocate their time to other valuable tasks.",

author = "Hsinchun Chen and Wingyan Chung and Xu, {Jennifer Jie} and Gang Wang and Yi Qin and Michael Chau",

note = "Funding Information: The Coplink project was funded by the National Institute of Justice and the National Science Foundation.",

year = "2004",

month = apr,

doi = "10.1109/MC.2004.1297301",

language = "English (US)",

volume = "37",

pages = "50--56",

journal = "Computer",

issn = "0018-9162",

publisher = "IEEE Computer Society",

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AU - Chung, Wingyan

AU - Xu, Jennifer Jie

AU - Wang, Gang

AU - Qin, Yi

AU - Chau, Michael

N1 - Funding Information: The Coplink project was funded by the National Institute of Justice and the National Science Foundation.

PY - 2004/4

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N2 - A general framework for crime data mining that draws on experience gained with the Coplink project at the University of Arizona is presented. By increasing efficiency and reducing errors, this scheme facilitates police work and enables investigators to allocate their time to other valuable tasks.

AB - A general framework for crime data mining that draws on experience gained with the Coplink project at the University of Arizona is presented. By increasing efficiency and reducing errors, this scheme facilitates police work and enables investigators to allocate their time to other valuable tasks.

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JO - Computer

JF - Computer

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Crime data mining: A general framework and some examples

Abstract

ASJC Scopus subject areas

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