多个术语基础的整合:使用层次结构结构的多视图对齐方法
Peihong Hu1, Qi Ye1, Weiyan Zhang1
1School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China.
Bioinformatics (Oxford, England)
|November 16, 2023
概括
本研究引入了一种新的多视图对齐方法,通过考虑它们的等级结构来协调医疗术语. 该方法提高了识别重叠术语的准确性,提高了医疗信息获取.
科学领域:
- 医疗信息学 医疗信息学
- 计算语言学 计算语言学
- 生物信息学是一种生物信息学.
背景情况:
- 存在多个医学术语基础,导致多余的术语和阻碍信息获取.
- 现有的方法与术语之间的语义和层次差异作斗争.
- 协调医疗术语对于统一的框架和全面的数据访问至关重要.
研究的目的:
- 开发一种用于调整异质医学术语的新方法.
- 解决医疗术语中不同层次结构的挑战.
- 改进跨不同医学知识库的重叠术语的识别.
主要方法:
- 一种多视图对齐方法,包含术语层次结构.
- 使用基于BERT的模型来捕捉递归层次关系.
- 考虑互动信息,包括姓名,邻居和等级.
主要成果:
- 拟议的方法在绘制医疗开放术语方面优于基线方法.
- 在Hits@1和Hits@10指标中实现了2%的改进.
- 在处理语义和结构异质性的证明有效性.
结论:
- 多视角对齐方法有效地通过利用等级结构来协调医疗术语.
- 这种方法提高了术语映射的准确性,促进了医疗数据的更好的整合.
- 这种方法为统一不同的医学知识库提供了一个有希望的解决方案.
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