中心性
度量(数据仓库)
索引(排版)
秩(图论)
GSM演进的增强数据速率
数学
统计
计算机科学
组合数学
数据挖掘
人工智能
万维网
作者
Jin Zhou,Yanqi Zhang,Jun-an Lu,Guanrong Chen
出处
期刊:IEEE transactions on systems, man, and cybernetics
[Institute of Electrical and Electronics Engineers]
日期:2024-01-23
卷期号:54 (5): 2757-2764
标识
DOI:10.1109/tsmc.2024.3349407
摘要
A new edge centrality measure, connectivity rank index (CRI), is proposed based on the effect of an edge on the network algebraic connectivity. Compared with the existing indices, the CRI can determine the importance of a present edge as well as an absent edge. For large-scale networks, the algorithm based on original CRI definition has high-time complexity. Therefore, an approximation algorithm is designed using the eigenvector elements corresponding to the second smallest Laplacian eigenvalue. This algorithm can identify the most influential edges and the least influential ones easily, which reduces the time complexity from the exhaustive searching scheme with $O(N^{5})$ to $O(N^{3})$ in a network of size $N$ . Some examples are shown to verify the effectiveness of the algorithm and the theoretical results.
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