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Closure Coefficient in Complex Directed Networks

机译:复合系数在复杂的网络中

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摘要

The 3-clique formation, a natural phenomenon in real-world networks, is typically measured by the local clustering coefficient, where the focal node serves as the centre-node in an open triad. The local closure coefficient provides a novel perspective, with the focal node serving as the end-node. It has shown some interesting properties in network analysis, yet it cannot be applied to complex directed networks. Here, we propose the directed closure coefficient as an extension of the closure coefficient in directed networks, and we extend it to weighted and signed networks. In order to better use it in network analysis, we introduce further the source closure coefficient and the target closure coefficient. Our experiments show that the proposed directed closure coefficient provides complementary information to the classic directed clustering coefficient. We also demonstrate that adding closure coefficients leads to better performance in link prediction task in most directed networks.
机译:在现实网络中的三分构造,一种自然现象,通常由本地聚类系数测量,其中焦点节点用作开放式三合会中的中心节点。 本地闭合系数提供了一种新颖的视角,其中焦点用作端节点。 它在网络分析中显示了一些有趣的属性,但它不能应用于复杂的针对网络。 这里,我们将指向的闭合系数提出作为指向网络中的闭合系数的延伸,并且我们将其扩展为加权和签名网络。 为了更好地使用它在网络分析中,我们进一步介绍了源关闭系数和目标闭合系数。 我们的实验表明,所提出的指向闭合系数为经典指示的聚类系数提供互补信息。 我们还证明,添加闭合系数导致在大多数针对网络中的链路预测任务中的更好性能。

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