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• W2969945377 endingPage "122259" @default.
• W2969945377 startingPage "122259" @default.
• W2969945377 abstract "Community structures contain important information of social networks. In most applications, mining community structures would be helpful for people to analyze networks. Typically, genetic algorithm is an effective approach to detect communities. At present, there are two kinds of genetic encoding methods: SGR (Tasgin et al., 2008) and LAR (Pizzuti, 2008) and both have some shortages, which always lead to premature convergence. Based on this, we proposed a new matrix encoding method for community detection, which contains total information of community clustering. We also designed crossover and mutation operator. According to the experiments, our method performed effectively." @default.
• W2969945377 created "2019-08-29" @default.
• W2969945377 creator A5042416229 @default.
• W2969945377 creator A5051562109 @default.
• W2969945377 date "2019-12-01" @default.
• W2969945377 modified "2023-09-30" @default.
• W2969945377 title "A new genetic algorithm for community detection using matrix representation method" @default.
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• W2969945377 doi "https://doi.org/10.1016/j.physa.2019.122259" @default.
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