DocumentCode :
265034
Title :
A Hierarchical Agglomerative Algorithm of Community Detecting in Social Network Based on Enhanced Similarity
Author :
Bing Kong ; Lei Li ; Lihua Zhou ; Chongming Bao
Author_Institution :
Sch. of Inf., Yunnan Univ., Kunming, China
Volume :
1
fYear :
2014
fDate :
26-27 Aug. 2014
Firstpage :
396
Lastpage :
400
Abstract :
Hierarchical agglomerative algorithm is widespread used in community detection of social networks. This paper explores an enhanced similarity which is based on interactive behavior of social members. The enhanced similarity expands the concept of similarity from vertexes to communities in the social network. Furthermore, the hierarchical agglomerative algorithm has been applied and the enhanced similarity of communities will be recalculated because of change of communities along with the agglomerative process. The experimental results show that our algorithm can well detect communities which well fitted the real communities in a social network.
Keywords :
social networking (online); community detection; enhanced similarity; hierarchical agglomerative algorithm; social network; Algorithm design and analysis; Clustering algorithms; Communities; Educational institutions; Reliability theory; Social network services; community detection; enhanced similarity; hierarchical agglomerative algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Human-Machine Systems and Cybernetics (IHMSC), 2014 Sixth International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4799-4956-4
Type :
conf
DOI :
10.1109/IHMSC.2014.103
Filename :
6917386
Link To Document :
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