title: |
A Knowledge Discovery Approach to Supporting Crime Prevention |
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publication: |
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part of series: |
Advances in Intelligent Systems Research | |
ISBN: |
978-90-78677-01-7 | |
ISSN: |
1951-6851 | |
DOI: |
doi:10.2991/jcis.2006.146 (how to use a DOI) | |
author(s): |
Sheng-Tun Li, Fu-Ching Tsai, Shu-Ching Kuo, Yi-Chung Cheng |
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corresponding author: |
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publication date: |
October 2006 |
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keywords: |
Trend discovery, crime prevention,self-organizing map, fuzzy theory. |
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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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copyright: |
©
Atlantis Press. This article is distributed under the
terms of the Creative Commons Attribution License, which permits
non-commercial use, distribution and reproduction in any medium,
provided the original work is properly cited. |
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full text: |