Proceedings of the 9th Joint International Conference on Information Sciences (JCIS-06)

A Knowledge Discovery Approach to Supporting Crime Prevention

Authors
Sheng-Tun Li 0, Fu-Ching Tsai, Shu-Ching Kuo, Yi-Chung Cheng
Corresponding Author
Sheng-Tun Li
0Institute of Information Management National Cheng Kung Univ
Available Online October 2006.
DOI
https://doi.org/10.2991/jcis.2006.146How to use a DOI?
Keywords
Trend discovery, crime prevention,self-organizing map, fuzzy theory.
Abstract
The main objective of this study is developing a linguistic cluster model in order to meet the public security index requirement and extract crime rule in time series. In contrast to the current studies in crime theory which mostly rely on traditional behavior science, we turned to a hybrid approach to overcome the hurdle of linguistic clustering in original SOM model.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
Part of series
Advances in Intelligent Systems Research
Publication Date
October 2006
ISBN
978-90-78677-01-7
ISSN
1951-6851
DOI
https://doi.org/10.2991/jcis.2006.146How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Sheng-Tun Li
AU  - Fu-Ching Tsai
AU  - Shu-Ching Kuo
AU  - Yi-Chung Cheng
PY  - 2006/10
DA  - 2006/10
TI  - A Knowledge Discovery Approach to Supporting Crime Prevention
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/jcis.2006.146
DO  - https://doi.org/10.2991/jcis.2006.146
ID  - Li2006/10
ER  -