Title
Overlapping community detection in complex networks using symmetric binary matrix factorization.
Abstract
Discovering overlapping community structures is a crucial step to understanding the structure and dynamics of many networks. In this paper we develop a symmetric binary matrix factorization model to identify overlapping communities. Our model allows us not only to assign community memberships explicitly to nodes, but also to distinguish outliers from overlapping nodes. In addition, we propose a modified partition density to evaluate the quality of community structures. We use this to determine the most appropriate number of communities. We evaluate our methods using both synthetic benchmarks and real-world networks, demonstrating the effectiveness of our approach.
Year
DOI
Venue
2013
10.1103/PhysRevE.87.062803
PHYSICAL REVIEW E
DocType
Volume
Issue
Journal
87
6
ISSN
Citations 
PageRank 
1539-3755
26
0.96
References 
Authors
0
3
Name
Order
Citations
PageRank
Zhong-Yuan Zhang11075.72
Yong Wang257546.58
Yong-Yeol Ahn32124138.24