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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和最重要的功能,以提取节点之间的功能关系。在过去几年中,社区检测问题已经在优化函数,纽曼 - Girvan模块化方面进行了重新制定,这应该将网络分区的质量表达到社区。从最近的模块化优化调查开始,指出存在对其适用性严重限制的解决限制的存在,我们讨论了在社区检测中使用质量功能的一般问题。我们的主要结论是,质量功能可用于将具有相同数量数量的分区进行比较,而具有不同数量的模块的分区的比较并不直接,并且可能导致含糊不清。

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