Identification of vital nodes based on global and local features in hypergraphs

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The LGK method enhances the identification of critical nodes, showing significant advantages over previous methods.
In empirical evaluations, LGK demonstrated improved accuracy and reduced time complexity in identifying nodes.
Analysis was based on the K-shell decomposition method, integrating both global and local features.
This approach highlights the potential of hypergraphs in effective representation of complex systems and relationships.

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New method LGK improves accuracy and reduces time complexity in identifying critical nodes in hypergraphs.

Liang et al. (2025) studied this question.

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