Enhancing the Efficiency of Unsupervised Network Alignment Using Quotient Graph
Network alignment, a foundational technique for cross-domain applications such as recommendation systems and knowledge fusion, faces significant challenges in balancing computational efficiency and alignment accuracy. Although graph neural networks (GNNs) effectively capture structural and semantic...
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| Hauptverfasser: | , |
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| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
IEEE
2025-01-01
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| Schriftenreihe: | IEEE Access |
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| Online-Zugang: | https://ieeexplore.ieee.org/document/10918943/ |
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