DocumentCode :
124257
Title :
A New Method for Community Detection Using Seed Nodes
Author :
Chang Su ; Yukun Wang ; Lan Zhang
Author_Institution :
Coll. of Comput. Sci. & Technol., Chongqing Univ. of Post & Telecommun., Chongqing, China
Volume :
2
fYear :
2014
fDate :
11-14 Aug. 2014
Firstpage :
429
Lastpage :
435
Abstract :
Large-scale social networks emerged rapidly in recent years. Social networks have become complex networks. The structure of social networks is an important research area and has attracted much scientific interest. Community is an important structure in social networks. In this paper, we propose a community detection algorithm based on seed nodes. First, we introduce how to find seed nodes based on random walk. Then we combine the algorithm with order statistics theory to find community structure. We apply our algorithm in three classical data sets and compare to other algorithms. Our community detection algorithm is proved to be effective in the experiments. Our algorithm also has applications in data mining and recommendations.
Keywords :
data analysis; data mining; social networking (online); statistical analysis; community detection algorithm; community structure; complex networks; data mining; data recommendations; data sets; large-scale social networks; order statistics theory; random walk; seed nodes; Algorithm design and analysis; Clustering algorithms; Communities; Detection algorithms; Educational institutions; Social network services; Software algorithms; Community structure; Order statistics; Random walk; Seed nodes; Social network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Web Intelligence (WI) and Intelligent Agent Technologies (IAT), 2014 IEEE/WIC/ACM International Joint Conferences on
Conference_Location :
Warsaw
Type :
conf
DOI :
10.1109/WI-IAT.2014.129
Filename :
6927656
Link To Document :
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