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Subsequence and distant supervision based active learning for relation extraction of Chinese medical texts
In recent years, relation extraction on unstructured texts has become an important task in medical research. However, relation extraction requires a large amount of labeled corpus, manually annotating sequences is time consuming and expensive. Therefore, efficient and economical methods for annotati...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9926422/ https://www.ncbi.nlm.nih.gov/pubmed/36788504 http://dx.doi.org/10.1186/s12911-023-02127-1 |