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Related Experiment Video

Updated: Sep 7, 2025

Modeling the Functional Network for Spatial Navigation in the Human Brain

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

Link importance assessment strategy based on improved k-core decomposition in complex networks.

Yongheng Zhang¹, Yuliang Lu², GuoZheng Yang¹

¹Electronic Engineering Institute, National University of Defense Technology, Heifei 230037, China.

Mathematical Biosciences and Engineering : MBE

|June 22, 2022

Summary

A new link importance assessment strategy, called t-shell, improves network destruction effectiveness. This method enhances target link importance assessment in complex networks without increasing computational complexity.

Keywords:

complex network k-core decomposition network robustness topological overlap

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Area of Science:

Network Science
Graph Theory
Computational Complexity

Background:

Assessing link importance is crucial for complex network analysis.
Betweenness centrality is effective but computationally expensive for large networks.
K-core decomposition offers a computationally efficient alternative for network analysis.

Purpose of the Study:

To develop a more effective and computationally efficient link importance assessment strategy for complex networks.
To introduce a novel indicator, the topological shell (t-shell), for link importance assessment.
To optimize network destruction strategies by improving target link identification.

Main Methods:

Incorporating topological overlap theory into existing k-core decomposition methods.
Developing the link topological shell (t-shell) indicator.
Conducting simulations on real-world and scale-free networks.

Main Results:

The t-shell based strategy demonstrates superior performance compared to the shell-based strategy.
The t-shell strategy achieves improved attack effects in network simulations.
Computational complexity is not increased with the proposed t-shell method.

Conclusions:

The t-shell indicator provides a more effective approach to target link importance assessment.
This method offers a promising direction for large-scale network destruction strategies.
The integration of topological overlap theory enhances network analysis tools.