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Structure-Aware Consistent Graph Autoencoder for Generative Content Review
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AI
DOI：10.1016/j.eswa.2026.134261.png)
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Abstract
En 中文
• A graph link prediction framework is developed for generative content review.
• Adaptive view augmentation preserves core connections in diverse graph structures.
• Cross-view consistency learning encourages consistent topology predictions.
Keywords:
Generative content review
Graph neural network
Graph self-supervised learning
Link prediction
Cross-view consistency learning
Journal
IF:
7.5
Papers:
3.0W
Citations:
10.2W
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