Discovering network community based on multi-objective optimization
Article
Article Title | Discovering network community based on multi-objective optimization |
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ERA Journal ID | 32139 |
Article Category | Article |
Authors | Huang, Faliang (Author), Zhang, Shichao (Author) and Zhu, Xiaofeng (Author) |
Journal Title | Journal of Software |
Journal Citation | 24 (9), pp. 2062-2077 |
Number of Pages | 16 |
Year | 2013 |
Place of Publication | Beijing, China |
ISSN | 1796-217X |
Digital Object Identifier (DOI) | https://doi.org/10.3724/SP.J.1001.2013.04400 |
Web Address (URL) | http://www.jos.org.cn/1000-9825/4400.htm |
Abstract | Community discovery is an important task in mining complex networks, and has important theoretical and application value in the terrorist organization identification, protein function prediction, public opinion analysis, etc. However, existing metrics used to measure quality of network communities are data dependent and have coupling relations, and the community discovery algorithms based on optimizing just one metric have a lot of limitations. To address the issues, the task to discover network communities is formalized as a multi-objective optimization problem. An algorithm, MOCD-PSO, is used to discover network communities based on multi-objective particle swarm optimization, which constructs objective function with modularity Q, MinMaxCut and silhouette. The experimental results show that the proposed algorithm has good convergence and can find Pareto optimal network communities with relatively well uniform and dispersive distribution. In addition, compared with the classical algorithms based on single objective optimization (GN, GA-Net) and multi-objective optimization (MOGA-Net, SCAH-MOHSA), the proposed algorithm requires no input parameters and can discover the higher-quality community structure in networks. |
Keywords | communities mining; complex network; multi-objective particle swarm optimization |
ANZSRC Field of Research 2020 | 400604. Network engineering |
400904. Electronic device and system performance evaluation, testing and simulation | |
350715. Quality management | |
Public Notes | © 2013 ISCAS. |
Byline Affiliations | Fujian Normal University, China |
Guangxi Normal University, China | |
University of Queensland | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q21vw/discovering-network-community-based-on-multi-objective-optimization
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