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首页> 外文期刊>PLoS One >Overlapping community detection in networks based on link partitioning and partitioning around medoids
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Overlapping community detection in networks based on link partitioning and partitioning around medoids

机译:基于链接分区和麦细分区分区的网络中的重叠社区检测

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摘要

In this paper, we present a new method for detecting overlapping communities in networks with a predefined number of clusters called LPAM (Link Partitioning Around Medoids). The overlapping communities in the graph are obtained by detecting the disjoint communities in the associated line graph employing link partitioning and partitioning around medoids which are done through the use of a distance function defined on the set of nodes. We consider both the commute distance and amplified commute distance as distance functions. The performance of the LPAM method is evaluated with computational experiments on real life instances, as well as synthetic network benchmarks. For small and medium-size networks, the exact solution was found, while for large networks we found solutions with a heuristic version of the LPAM method.
机译:在本文中,我们提出了一种用于检测具有名为LPAM的预定数量的群集的网络中的重叠社区的新方法(链接分区谱图)。 通过检测使用链路分区和通过使用在节点集合上定义的距离函数来完成的联接的线图中的脱编社区来获得图表中的重叠社区。 我们认为通勤距离和放大的通勤距离作为距离函数。 LPAM方法的性能被评估为在实际实例上的计算实验,以及合成网络基准测试。 对于中小型网络,找到确切的解决方案,而对于大型网络,我们发现具有LPAM方法的启发式版本的解决方案。

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