Auto-Contractive Maps and Minimal Spanning Tree: Organization of Complex Datasets on Criminal Behavior to Aid in the Deduction of Network Connectivity

  • Giulia Massini
  • Massimo Buscema


Using the Metropolitan Police Service Central Drug Trafficking Database (London, UK), the Auto-Contractive Map neural network technology is applied to identify unknown associations among individuals contained within it. Whilst a database may contain associations of known individuals, it may be mined to identify associations that are altogether unknown and unexpected. It is shown that individuals can be identified who belong to the same gang or drug trafficking circle. The results produce a profile that is mathematically justified and devoid of any political involvement. Key to this analysis is the organization of the datasets such that a meaningful analysis and interpretation can be made. This organization is described and illustrated using the drug trafficking data.


Drug Trafficking Police Operation Previous Offense Drug Seizure Previous Arrest 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.Semeion Research Center of Sciences of CommuicationRomeItaly

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