Extending CDFR for overlapping community detection

Publication Type:
Conference Proceeding
Citation:
Proceedings - 2018 1st International Conference on Data Intelligence and Security, ICDIS 2018, 2018, pp. 200 - 206
Issue Date:
2018-05-25
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© 2018 IEEE. In many real-world networks, a node often belongs to multiple communities. Therefore, overlapping community detection is an important task in social network analysis. CDFR is an efficient algorithm recently proposed for non-overlapping community detection. In this paper, CDFR is extended for overlapping community detection, and the extended algorithm is called as OCDFR. In OCDFR, CDFR is first called to obtain a non-overlapping community partition. Then, find the kth NGC (k=1, 2, 3,..) node for each node, and record the fuzzy relations between them. Based on the fuzzy relation between a node and its kth NGC, five decision methods are proposed to determine whether it can join the communities to which its kth NGC belongs. Experimental results on real-world networks and synthetic networks demonstrate that OCDFR is effective and highly competitive.
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