Title :
Comparison of Feature-Based Criminal Network Detection Models with k-Core and n-Clique
Author :
Ozgul, Fatih ; Erdem, Zeki ; Bowerman, Chris ; Atzenbeck, Claus
Author_Institution :
Dept. of Comput., Univ. of Sunderland, Sunderland, UK
Abstract :
Four group detection models (e.g. GDM, OGDM, SoDM and ComDM) are developed based on crime data features. These detection models are compared more common baseline SNA group detection algorithms. It is intended to find out, whether these four crime data specific group detection models can perform better than widely used k-core and n-clique algorithms. Two data sets which contain previously known criminal networks are used as testbeds.
Keywords :
graph theory; police data processing; social networking (online); SNA group detection algorithm; crime data features; crime data specific group detection model; feature based criminal network detection model; group detection model; k-core; n-clique; social network analysis; Computational modeling; Data mining; Data models; Drugs; Feature extraction; Social network services; Terrorism; criminal networks; detection; k-core; n-clique;
Conference_Titel :
Advances in Social Networks Analysis and Mining (ASONAM), 2010 International Conference on
Conference_Location :
Odense
Print_ISBN :
978-1-4244-7787-6
Electronic_ISBN :
978-0-7695-4138-9
DOI :
10.1109/ASONAM.2010.45
