通过双层嵌入,对时间知识图进行近似查询
Jiaxuan Liu1, Xinyi Duan2, Luyi Bai2
1Sydney Smart Technology College, Northeastern University, Qinhuangdao 066004, China.
Entropy (Basel, Switzerland)
|December 24, 2025
概括
本研究引入了一种新方法,用于在动态时间知识图 (TKG) 中进行近似查询. 两级近似查询 (TLAQ) 方法增强了图形嵌入,以获得更准确的结果.
科学领域:
- 计算机科学 计算机科学
- 人工智能的人工智能
- 数据科学数据科学数据科学
背景情况:
- 在现实世界的应用中,对知识图 (KG) 进行近似查询至关重要.
- 现有的方法主要针对静态的KG,忽视了它们的动态性质.
- 时间知识图 (TKG) 包含随时间变化的信息,这带来了独特的挑战.
研究的目的:
- 开发一种有效的方法,用于在时间知识图 (TKG) 中进行近似查询.
- 解决处理动态和时间感知数据的现有方法的局限性.
- 为了提高查询结果的准确性和相关性,从不断发展的KG.
主要方法:
- 为TKG提出了一种两级近似查询 (TLAQ) 方法.
- 增强图形卷积网络 (GCN) 固有矩阵,用于改进顶点和图形嵌入.
- 在顶点层面引入了关系可靠性和属性信任.
- 在图形层面进行统一的时间编码,以加强嵌入模型.
主要成果:
- TLAQ方法在处理TKG上的近似查询方面表现出有效性.
- 拟议的方法在实验评估中显示了与现有方法相比更好的性能.
- 两级嵌入策略成功地捕捉了时间动态和关系.
结论:
- TLAQ 方法为动态 TKG 中的近似查询提供了一个强大的解决方案.
- 用时间信息增强图形嵌入是提高查询准确性的关键.
- 这项工作有助于更高效,更有效地从不断变化的知识库中检索信息.
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