DocumentCode :
3383767
Title :
An effective community detection algorithm of the social networks
Author :
Yuan Huang ; Wei Hou ; Xiaowei Li ; Shaomei Li
Author_Institution :
Nat. Comput. Network & Inf. Security Adm. Center, Beijing, China
fYear :
2013
fDate :
23-25 March 2013
Firstpage :
824
Lastpage :
827
Abstract :
The traditional social network community detection algorithms generally lack of consideration of link attributes, and full expression using link attribute information model and mechanism. Aiming at this issue, this paper puts forward the community detection algorithm of social network through fusion the link and node attributes. We combine similarity of node attributes between adjacent nodes and link information, and define the similar weights. On this basis, the algorithm realizes community detection of the social network by combining condensation algorithm. Experiments show that effect of this algorithm about social network attribute is remarkable, obviously in attribute-distinct community.
Keywords :
social networking (online); attribute-distinct community; condensation algorithm; link attribute information model; node attributes; social network community detection algorithms; Algorithm design and analysis; Classification algorithms; Clustering algorithms; Communities; Detection algorithms; Image edge detection; Social network services;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Science and Technology (ICIST), 2013 International Conference on
Conference_Location :
Yangzhou
Print_ISBN :
978-1-4673-5137-9
Type :
conf
DOI :
10.1109/ICIST.2013.6747668
Filename :
6747668
Link To Document :
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