Towards accurate food safety risks prediction via context-enhanced heterogeneous GNN
Accurate prediction of food safety risks is crucial for protecting public health and optimizing regulatory processes. This study investigates the context-enhanced heterogeneous graph neural network (HGNN) to address the complexity of risk prediction. First, we devise a contrastive learning-based fea...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-06-01
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| Series: | Applied Food Research |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S277250222500232X |
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