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Nonlinear random walks on hypergraphs characterized by higher-order interactions
DOI:10.1016/j.ress.2026.112307.png)
Abstract
En 中文
• Captured nonlinear characteristics inherent in higher-order group interactions. • Broke through linear assumptions of transition probabilities in random walks. • Proposed a nonlinear random walk model on hypergraphs with higher-order interactions. • Validated superior performance in identifying critical nodes across real-world datasets.
Keywords:
nonlinear random walks
hypergraphs
higher-order interactions
critical node identification
Journal
R
IF:
11
Papers:
461
Citations:
0

