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CSE
2009
IEEE

Collaborative Mining in Multiple Social Networks Data for Criminal Group Discovery

9 years 9 months ago
Collaborative Mining in Multiple Social Networks Data for Criminal Group Discovery
—The hidden knowledge in social networks data can be regarded as an important resource for criminal investigations which can help finding the structure and organization of a criminal network. However such network based analysis has not been studied in an applied way and remains mostly a manual process. To assist inspectors and intelligence agencies discover this knowledge, we defined a new problem and then proposed a framework for automated network data analysis and deduction approach from multiple social networks by converting to transaction dataset, applying association mining, and statistical methods. By applying a game theory concept in a multi-agent model, we try to design a policy for knowledge discovery and inference fusion. This approach enables police stations to build and deploy P2P applications through a unified medium for finding criminals relationship and identifying suspicious guys.
Amin Milani Fard, Martin Ester
Added 20 May 2010
Updated 20 May 2010
Type Conference
Year 2009
Where CSE
Authors Amin Milani Fard, Martin Ester
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