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A position-aware attention model based on double-level contrastive learning for hyper-relational knowledge graph representation in emergency management

Xinzhi Wang Weijian Zhu Jiang Kai Xiangfeng Luo Jianqiang Huang

Journal of Safety Science and Resilience2026，Vol.7Issue(1)：P.143-153,11.

Journal of Safety Science and Resilience2026，Vol.7Issue(1)：P.143-153,11.DOI:10.1016/j.jnlssr.2025.100223

A position-aware attention model based on double-level contrastive learning for hyper-relational knowledge graph representation in emergency management

Xinzhi Wang ¹Weijian Zhu ¹Jiang Kai ²Xiangfeng Luo ¹Jianqiang Huang¹

作者信息

1. School of Computer Engineering and Science,Shanghai University,Shanghai,200444,China
2. China Academy of Electronics and Information Technology,Beijing,100045,China
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摘要

关键词

Emergency management/Link prediction/Hyper-relational knowledge graph/Contrastive learning/Position information

分类

信息技术与安全科学

引用本文复制引用

Xinzhi Wang,Weijian Zhu,Jiang Kai,Xiangfeng Luo,Jianqiang Huang..A position-aware attention model based on double-level contrastive learning for hyper-relational knowledge graph representation in emergency management[J].Journal of Safety Science and Resilience,2026,7(1):P.143-153,11.

基金项目

supported in part by the National Key Research and Development Program of China under the grant No.2021YFC3300602 （）

the Outstanding Academic Leader Project of Shanghai under the grant No.20XD1401700 （）

the National Natural Science Foundation of China under the grant No.91746203. （）

Journal of Safety Science and Resilience

ISSN：2096-7527

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