DocumentCode :
3564296
Title :
A new approach for detection of common communities in a social network using graph mining techniques
Author :
Rao, Bapuji ; Mitra, Anirban
Author_Institution :
Dept. of CSE & IT, V.I.T.A.M., Berhampur, India
fYear :
2014
Firstpage :
1
Lastpage :
6
Abstract :
Community effect and inter community communication and relationship is one of the important aspects of social network analysis. Studying community detection and analyzing the behaviors of the communities can give us information about the group as well as about the actors in the group. Using graph mining techniques, knowledge extraction is possible from the community graph. In our work, we started with the discussion on related definitions and some of the available algorithms for community detection in social network. Further, we propose a new and simple algorithm for finding the community detection in a social network using graph techniques. An example verifies about the strength of the proposed algorithm.
Keywords :
data mining; graph theory; social sciences computing; common community detection; community effect; community graph; graph mining techniques; inter community communication; knowledge extraction; social network analysis; Communities; Community Graph; Community Head; Graph Incidence Matrix; Seed Number;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
High Performance Computing and Applications (ICHPCA), 2014 International Conference on
Print_ISBN :
978-1-4799-5957-0
Type :
conf
DOI :
10.1109/ICHPCA.2014.7045335
Filename :
7045335
Link To Document :
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