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| Content Provider | PubMed Central |
|---|---|
| Author | Li, Zhenping Zhang, Xiang-sun Wang, Rui-sheng Liu, Hongwei Zhang, Shihua |
| Editor | Zhu, Dongxiao |
| Copyright Year | 2013 |
| Abstract | Identification of communities in complex networks is an important topic and issue in many fields such as sociology, biology, and computer science. Communities are often defined as groups of related nodes or links that correspond to functional subunits in the corresponding complex systems. While most conventional approaches have focused on discovering communities of nodes, some recent studies start partitioning links to find overlapping communities straightforwardly. In this paper, we propose a new quantity function for link community identification in complex networks. Based on this quantity function we formulate the link community partition problem into an integer programming model which allows us to partition a complex network into overlapping communities. We further propose a genetic algorithm for link community detection which can partition a network into overlapping communities without knowing the number of communities. We test our model and algorithm on both artificial networks and real-world networks. The results demonstrate that the model and algorithm are efficient in detecting overlapping community structure in complex networks. |
| Related Links | http://dx.doi.org/10.1371/journal.pone.0083739 |
| Starting Page | 83739 |
| File Format | |
| ISSN | 19326203 |
| e-ISSN | 19326203 |
| Journal | PLoS ONE |
| Issue Number | 12 |
| Volume Number | 8 |
| Language | English |
| Publisher | Public Library of Science |
| Publisher Date | 2013-12-01 |
| Access Restriction | Open |
| Rights Holder | Public Library of Science |
| Subject Keyword | Biochemistry, Genetics and Molecular Biology(all) Agricultural and Biological Sciences(all) Medicine(all) Research in Higher Education |
| Content Type | Text |
| Resource Type | Article |
| Subject | Multidisciplinary |
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