SPBERE:通过实体信息来促进基于跨度的管道生物医学实体和关系提取.
Chenglin Yang1, Jiamei Deng2, Xianlai Chen3
1Big Data Institute, Central South University, Changsha, 410083, China; School of Life Sciences, Central South University, Changsha, 410083, China.
Journal of biomedical informatics
|July 23, 2023
概括
这项研究引入了一种新的端到端方法,用于生物医学三重提取,有效地解决重叠实体和关系的挑战. 该方法提高了关系提取性能,为生物医学文本挖掘提供了更强大的解决方案.
科学领域:
- 生物医学文本挖掘技术
- 自然语言处理自然语言处理.
- 生物信息学是一种生物信息学.
背景情况:
- 三胞胎提取对于理解生物医学关系至关重要.
- 现有的联合方法在与生物医学文本中常见的重叠实体和关系作斗争.
- 管道方法可能会受到错误传播的影响.
研究的目的:
- 提出一种新的终端到终端管道方法,用于生物医学三重提取.
- 为了有效地检测重叠的三胞胎和关系.
- 提高生物医学文献中关系提取的准确性.
主要方法:
- 基于跨度的检测策略列举了候选跨度和实体对,以识别重叠的三胞胎.
- 单独的实体和关系模型捕获了上下文化的表示.
- 从实体模型中获得的实体信息很早就被融入到关系模型中,没有外部知识.
主要成果:
- 拟议的方法在DDI和CHEMPROT数据集上的关系提取中实现了3.5%-3.7%的F1得分的绝对改善.
- 证明了基于跨度的方法在重叠三重组检测中的有效性.
- 展示了上下文化表示和早期实体信息融合的好处.
结论:
- 新型管道方法通过有效处理重叠的实体和关系来增强生物医学三重提取.
- 基于跨度的检测和实体信息的早期融合是改善关系提取性能的关键.
- 这种方法为生物医学文本挖掘任务提供了显著的进步.
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