Node Significance Analysis in Complex Networks Using Machine Learning and Centrality Measures

Node Significance Analysis in Complex Networks Using Machine Learning and Centrality Measures

The study addresses the limitations of traditional centrality measures in complex networks, especially in disease-spreading situations, due to their inability to fully grasp the intricate connection between a node’s functional importance and structural attributes. To tackle this issue, th...

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Bibliographic Details
Main Authors: Koduru Hajarathaiah, Murali Krishna Enduri, Satish Anamalamudi, Ashu Abdul, Jenhui Chen
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Complex networks
influential nodes
local centralities
machine learning techniques
Online Access:https://ieeexplore.ieee.org/document/10401904/

Internet

https://ieeexplore.ieee.org/document/10401904/

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