Subgraph-Aware Joint Modeling for Graph Classification via Efficient Frequent Pattern Mining and Fusion
This paper proposes a subgraph-aware classification framework that integrates efficient frequent subgraph mining with graph neural networks (GNNs) to address the limitations of existing GNNs in capturing explicit local structures. Specifically,we first introduce an improved mining strategy to extrac...
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| Główni autorzy: | , , , , , , , |
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| Format: | Artigo |
| Język: | Inglês |
| Wydane: |
IEEE
2025-01-01
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| Seria: | IEEE Access |
| Hasła przedmiotowe: | |
| Dostęp online: | https://ieeexplore.ieee.org/document/11141440/ |
| Etykiety: |
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