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.
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