Title :
Mining community in social network using call detail records
Author :
Hu, Zhiwen ; Wang, Xianming ; Xu, Ke
Author_Institution :
Oujiang Coll., Wenzhou Univ., Wenzhou, China
Abstract :
With the popularity of mobile devices and wireless technologies, mobile social network systems are increasingly available. In this paper we propose a new algorithm called Community Detection algorithm for mining interesting communities or groups in a Campus Mobile Social Network (CMSN). The proposal algorithm is composed of two main components, an algorithm for community partition and an algorithm for selecting small communities to combine into a big community. Empirical studies on a campus mobile social network show that performance of the proposal algorithm is better than the state-of-the-art Newman Clustering algorithm for mining community in CMSN.
Keywords :
data mining; mobile computing; pattern clustering; social networking (online); CMSN; Newman clustering algorithm; big community; call detail records; campus mobile social network system; community detection algorithm; community mining; community partition algorithm; small community selection algorithm; Clustering algorithms; Communities; Data mining; Mobile communication; Mobile computing; Partitioning algorithms; Social network services; Campus Mobile Network; Community Detection; Social network;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2012 9th International Conference on
Conference_Location :
Sichuan
Print_ISBN :
978-1-4673-0025-4
DOI :
10.1109/FSKD.2012.6233712