基于嵌入的跨语言时间知识图的实体对齐
Luyi Bai1, Nan Li1, Guishun Li1
1School of Computer and Communication Engineering, Northeastern University (Qinhuangdao), Qinhuangdao 066004, China.
概括
这项研究介绍了CTEA,一种用于跨语言时间知识图中的实体对齐的新方法. 通过整合时间动态和跨语言信息,CTEA提高了对准准确度,优于现有的方法.
科学领域:
- 知识图 建筑 建筑知识图
- 人工智能的人工智能
- 自然语言处理自然语言处理.
背景情况:
- 现有的实体对齐方法主要针对静态知识图.
- 实体关系和属性的时间特征经常被忽视,导致对齐不准确.
- 在时间知识图中跨语言实体对齐仍然是一个未被充分探索的研究领域.
研究的目的:
- 为跨语言的时间知识图提出一个新的实体对齐方法.
- 为了解决实体对齐中的静态和非时间方法的局限性.
- 提高跨不同语言和时间维度匹配实体的准确性和可靠性.
主要方法:
- 开发了CTEA,这是一个联合嵌入模型,结合了实体,关系和属性嵌入.
- 利用图形卷积网络 (GCN) 和TransE进行嵌入生成.
- 集成距离和相似性计算以提高跨语言对齐可靠性.
主要成果:
- CTEA模型在实体调整任务中表现得更好.
- 实验结果显示,与最先进的方法相比,Hits@m和MRR的增加约为0.82.4个百分点.
- 提出的方法有效地处理知识图中的时间动态和跨语言复杂性.
结论:
- CTEA为跨语言时间知识图中的实体对齐提供了一个强大的解决方案.
- 联合嵌入方法和综合相似性措施提高了对齐精度.
- 这项工作有助于推进知识图表完成和管理领域.
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