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
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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.
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Proceedings
9th Joint International Conference on Information Sciences (JCIS-06)
Publication Date
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ISBN
978-90-78677-01-7
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  - NaN/NaN
DA  - NaN/NaN
TI  - A Knowledge Discovery Approach to Supporting Crime Prevention
BT  - 9th Joint International Conference on Information Sciences (JCIS-06)
PB  - Atlantis Press
UR  - https://doi.org/10.2991/jcis.2006.146
DO  - https://doi.org/10.2991/jcis.2006.146
ID  - LiNaN/NaN
ER  -