DocumentCode :
3647839
Title :
An ACO inspired weighting approach for the spectral partitioning of co-authorship networks
Author :
Pavel Krömer;Václav Snášel;Jan Platoš;Miloš Kudělka;Zdeněk Horák
Author_Institution :
Department of Computer Science, FEECS, VŠ
fYear :
2012
fDate :
6/1/2012 12:00:00 AM
Firstpage :
1
Lastpage :
7
Abstract :
Spectral partitioning is a well known method in the area of graph and matrix analysis. Several approaches based on spectral partitioning and spectral clustering were used to detect structures in real world networks and databases. In this paper, we use the spectral partitioning to detect communities in a co-authorship network. The partitioning depends heavily on the weighting of the underlying network. We use an intuitive weighting scheme based on the ant colony optimization and show the communities found by spectral partitioning when using the ACO inspired weighting and when using trivial weighting based on the number of interactions between the authors.
Keywords :
"Communities","Social network services","Joints","Partitioning algorithms","Clustering algorithms","Cost accounting","Conferences"
Publisher :
ieee
Conference_Titel :
Evolutionary Computation (CEC), 2012 IEEE Congress on
Print_ISBN :
978-1-4673-1510-4
Type :
conf
DOI :
10.1109/CEC.2012.6252863
Filename :
6252863
Link To Document :
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