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A Genetic Algorithm with Local Search Strategy for Improved Detection of Community Structure

机译:改进局部结构检测的局部搜索遗传算法

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摘要

On the basis of modularity optimization, a genetic algorithm is proposed to detect, community structure in networks by defining a local search operator: The local search operator emphasizes two features: one is that the connected nodes in a network should be located in the same community, while the other is "local selection" inspired by the mechanisms of efficient message delivery underlying the small-world phenomenon. The results of community detection for some classic networks, such as Ucinet and Pajek networks, indicate that our algorithm. achieves better community structure than. other methodologies based on modularity optimization, such. as the algorithms based on betweenness analysis, simulated annealing or Tasgin and Bingol's genetic algorithm.
机译:在模块化优化的基础上,提出了一种遗传算法,通过定义本地搜索算子来检测网络中的社区结构:本地搜索算子强调两个特征:一个是网络中的连接节点应位于同一社区中。 ,而另一种是“本地选择”,其灵感来自小世界现象背后的有效消息传递机制。某些经典网络(例如Ucinet和Pajek网络)的社区检测结果表明我们的算法。比实现更好的社区结构。其他基于模块化优化的方法,例如。作为基于中介度分析,模拟退火或Tasgin和Bingol遗传算法的算法。

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