用并行遗传算法搜索重叠社区
Search for overlapped communities by parallel genetic algorithms
摘要：
在过去的十年中，复杂网络的广泛范围导致了快速的发展。在这一领域，特别感兴趣的是对群落结构的研究。这种类型的结构的分析需要形式化的直观概念的社区和所获得的结果的指标的定义。为了达到这一目标，已经提出了许多算法。特别是，一个有趣的问题是重叠社区的搜索，这是领域似乎非常有趣的解决方案的基础上使用遗传算法。本文讨论的方法是基于并行实现的遗传算法，并显示了这种解决方案的性能优势。
英文摘要：
In the last decade the broad scope of complex networks has led to a rapid progress. In this area a particular interest has the study of community structures. The analysis of this type of structure requires the formalization of the intuitive concept of community and the definition of indices of goodness for the obtained results. A lot of algorithms has been presented to reach this goal. In particular, an interesting problem is the search of overlapped communities and it is field seems very interesting a solution based on the use of genetic algorithms. The approach discusses in this paper is based on a parallel implementation of a genetic algorithm and shows the performance benefits of this solution.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
