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Improving the accuracy of the k-shell method by removing redundant links: From a perspective of spreading dynamics

机译:通过消除冗余链接来提高 k -shell方法的准确性:从传播动力学的角度

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摘要

Recent study shows that the accuracy of the k -shell method in determining node coreness in a spreading process is largely impacted due to the existence of core-like group, which has a large k -shell index but a low spreading efficiency. Based on the analysis of the structure of core-like groups in real-world networks, we discover that nodes in the core-like group are mutually densely connected with very few out-leaving links from the group. By defining a measure of diffusion importance for each edge based on the number of out-leaving links of its both ends, we are able to identify redundant links in the spreading process, which have a relatively low diffusion importance but lead to form the locally densely connected core-like group. After filtering out the redundant links and applying the k -shell method to the residual network, we obtain a renewed coreness k s for each node which is a more accurate index to indicate its location importance and spreading influence in the original network. Moreover, we find that the performance of the ranking algorithms based on the renewed coreness are also greatly enhanced. Our findings help to more accurately decompose the network core structure and identify influential nodes in spreading processes.
机译:最近的研究表明,k-shell方法在扩展过程中确定节点核心性的准确性受k-shell指数大但扩展效率低的类核心组的影响。通过对现实网络中类核心组的结构分析,我们发现类核心组中的节点相互密集连接,而该组中的出节点很少。通过根据两端的外出链路数量定义每个边缘的扩散重要性度量,我们可以识别扩展过程中的冗余链路,这些冗余链路的扩散重要性相对较低,但会导致局部密集地形成连接的类核群。在过滤掉冗余链路并将k-shell方法应用于残差网络之后,我们为每个节点获得了更新的核心度k s ,这是一个更准确的指标,用于指示其在网络中的位置重要性和扩展影响原始网络。此外,我们发现基于更新的核心性的排序算法的性能也大大提高了。我们的发现有助于更准确地分解网络核心结构,并确定传播过程中的影响节点。

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