Cited by Identifying influential nodes based on hybrid centrality of receivers in the second-order dissemination

Finding influential nodes via graph embedding and hybrid centrality in complex networks DOI

Aman Ullah, Muhammad Ali Naeem

Chaos Solitons & Fractals, Journal Year: 2025, Volume and Issue: 194, P. 116151 - 116151

Published: Feb. 25, 2025

Language: Английский

Citations

Locating influential nodes in hypergraphs via fuzzy collective influence DOI

S. F. Zhang,

Xiaoyan Yu, Gui‐Quan Sun

et al.

Communications in Nonlinear Science and Numerical Simulation, Journal Year: 2025, Volume and Issue: unknown, P. 108574 - 108574

Published: Jan. 1, 2025

Language: Английский

Citations

Design and Implementation of Node Degree Centrality Computing of Network Security Database Based on Knowledge Graph DOI

Chao Wu,

Feng Wu

Security and Privacy, Journal Year: 2025, Volume and Issue: 8(1)

Published: Jan. 1, 2025

ABSTRACT With the development and popularization of network technology, security issues are increasingly being valued. The application knowledge graph technology in can significantly enhance level protection, assist users relevant departments understanding overall trends vulnerabilities, swiftly identify respond to threats. To improve analysis response capabilities threats, developing methods for identifying key nodes is urgent. This research focuses on degree centrality calculation method a database based graphs. We propose novel approach computing node within graph‐based database. comprises two main components: weight score calculation. Additionally, we have developed importance ranking module derived from CVE database, providing faster more accurate solution compared manual methods. then discuss significant value promising prospects field protection future work.

Language: Английский

Citations

Directional Node Strength Entropy centrality: Ranking influential nodes in complex networks DOI