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Quality functions in community detection

机译:社区检测中的质量功能

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Community structure represents the local organization of complex networks and the single most important feature to extract functional relationships between nodes. In the last years, the problem of community detection has been reformulated in terms of the optimization of a function, the Newman-Girvan modularity, that is supposed to express the quality of the partitions of a network into communities. Starting from a recent critical survey on modularity optimization, pointing out the existence of a resolution limit that poses severe limits to its applicability, we discuss the general issue of the use of quality functions in community detection. Our main conclusion is that quality functions are useful to compare partitions with the same number of modules, whereas the comparison of partitions with different numbers of modules is not straightforward and may lead to ambiguities.
机译:社区结构代表了复杂网络的本地组织,是提取节点之间功能关系的最重要的单一功能。在过去的几年中,社区检测问题已通过功能的优化(纽曼-吉尔万模块化)重新表述,该功能被认为可以表达将网络划分为社区的质量。从最近对模块化优化的重要调查开始,指出存在分辨率限制,该分辨率限制对其适用性提出了严格的限制,我们讨论了在社区检测中使用质量函数的一般性问题。我们的主要结论是,质量函数对于比较具有相同数量模块的分区非常有用,而具有不同模块数量的分区的比较不是直接的,并且可能导致歧义。

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