Aug 2026· International Journal of Machine Learning and Cybernetics· Vol 17· 0 citations· 48 references
TL;DR
Comprehensive evaluations on multiple real-world networks demonstrate KSvoterank’s superior performance in propagation scope and robustness, validating its utility for influence maximization and network robustness analysis.
A new node centrality—semi-clustering weighted LC (SWLC)—is proposed, from the perspective of synergizing node’s own attributes with its neighborhood structure, and is capable of effectively identifying critical nodes in complex networks.
Rong-Rong Yin, M. Shen, En-You Zhu et al.· Physica Scripta· 0 citations
Identifying influential nodes in complex networks is a fundamental problem in network science, with applications in epidemic control, information diffusion, and rumor spreading. K-shell decomposition is widely used due to its global perspective and linear time complexity. However, most K-shell based approaches are desi...
Shima Esfandiari, S. M. Fakhrahmad, Mohsen Raji· IEEE Access· 0 citations
The identification of influential nodes in directed networks is fundamental to diffusion analysis, network robustness assessment, and information recommendation. Owing to the asymmetry introduced by directed edges, conventional centrality methods often struggle to jointly characterize the local spreading range, higher-...
Identifying influential nodes in complex networks is a fundamental challenge in network science. This problem involves measuring the influence of nodes and identifying those that exert the greatest impact on network dynamics and information dissemination. Existing approaches can be broadly divided into two categories:...
Amir Sheikhahmadi, L. Tafakori, M. Jalili· ACM Computing Surveys· 0 citations
Spectral Efficiency Centrality (SEC), a temporal spectral centrality framework that quantifies node importance by evaluating the change in spectral radius caused by node removal across temporal snapshots, and ASEC, an efficient approximation based on Perron-Frobenius theory and first-order eigenvalue perturbation that...
This paper investigates whether entropy-based k-hop metrics capture aspects of structural node importance that are not emphasized by classical centrality measures. We compare degree and eigenvector centrality with two entropy-based measures, Entropy-Weighted Redundancy (EWR) and Normalized Entropy Density (NED), on thr...
Zsolt Valiskó, T. Balla, Csaba Biró· Proceedings of the 13th Inte...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
