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Dual Graph Convolutional Networks
DualGCN
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
A dual graph convolutional neural network jointly considers the two essential assumptions of semi-supervised learning: (1) local consistency and (2) global consistency. Accordingly, two convolutional neural networks are devised to embed the local-consistency-based and global-consistency-based knowledge, respectively.
Description and image from: Dual Graph Convolutional Networks for Graph-Based Semi-Supervised Classification
Papers archive 2025-07-28
1 shown of 1, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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Dual Graph Convolutional Networks for Aspect-based Sentiment Analysis 1 Aug 2021 · 1 repository
Tasks archive 2025-07-28
5 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
| Task | Papers |
|---|---|
| Aspect-Based Sentiment Analysis | 1 |
| Aspect-Based Sentiment Analysis (ABSA) | 1 |
| Dependency Parsing | 1 |
| Sentiment Analysis | 1 |
| Sentiment Classification | 1 |
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
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