A study on pharmaceutical text relationship extraction based on heterogeneous graph neural networks
Effective information extraction of pharmaceutical texts is of great significance for clinical research. The ancient Chinese medicine text has streamlined sentences and complex semantic relationships, and the textual relationships may exist between heterogeneous entities. The current mainstream rela...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
AIMS Press
2024-01-01
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| Series: | Mathematical Biosciences and Engineering |
| Subjects: | |
| Online Access: | https://www.aimspress.com/article/doi/10.3934/mbe.2024064?viewType=HTML |