A Method for Predicting Links in Complex Networks by Integrating Enclosure Subgraphs With High-Frequency Graph Information
Link prediction in complex networks, crucial for uncovering hidden or upcoming links between nodes and widely applicable in fields such knowledge graphs, faces challenges with current techniques. Predominantly, graph neural networks (GNN) based methods focus on learning node representations and use...
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| Principais autores: | , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
IEEE
2024-01-01
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| coleção: | IEEE Access |
| Assuntos: | |
| Acesso em linha: | https://ieeexplore.ieee.org/document/10517583/ |
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