SAQE: Complex Logical Query Answering via Semantic-Aware Representation Learning

doi:10.1109/TKDE.2025.3603877

	SAQE: Complex Logical Query Answering via Semantic-Aware Representation Learning
	Cao, Zongsheng 1,2,3; Xu, Qianqian 4; Yang, Zhiyong 5; He, Yuan 6; Cao, Xiaochun 7; Huang, Qingming 4,8,9
	2025-11-01
发表期刊	IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
ISSN	1041-4347
卷号	37 期号:11 页码:6651-6665
摘要	Performing complex First-Order Logic (FOL) queries on knowledge graphs is crucial for advancing knowledge reasoning. Knowledge graphs encapsulate rich semantic interactions among entities, encompassing both explicit structural knowledge represented by triples (e1,r,e2) and implicit relational knowledge through multi-hop paths (e1(r1)->& ctdot;e3 & ctdot;(r2)-> e2). Traditional models often focus solely on either triple-level or path-level knowledge, overlooking the benefits of integrating both to enhance logic query answering. This oversight leads to suboptimal representation learning and inefficient query reasoning. To overcome these challenges, we introduce a new Semantic-Aware representation learning model for Query-answering Embeddings (SAQE). Specifically, SAQE employs a joint learning approach that integrates triple-level and path-level knowledge semantics and captures both explicit and implicit contextual nuances within the knowledge graph, yielding more accurate and contextually relevant representations. To efficiently handle the large combinatorial search spaces in FOL reasoning, we propose a novel hierarchical reasoning optimization strategy by a multi-hop tree thus optimizing subqueries rooted at variable nodes in a divide-and-conquer manner. Theoretical analysis confirms that SAQE effectively supports various types of FOL reasoning and enhances generalizations for query answering. Extensive experiments demonstrate that our model achieves state-of-the-art performance across several established datasets.
关键词	Cognition Knowledge graphs Representation learning Semantics Optimization Logic Accuracy Data mining Training Artificial intelligence Knowledge graph logic query answering semantic-aware learning hierarchical reasoning optimization
DOI	10.1109/TKDE.2025.3603877
收录类别	SCI
语种	英语
资助项目	National Key R#x0026;D Program of China[2018AAA0102000] ; National Natural Science Foundation of China[62236008] ; National Natural Science Foundation of China[62441232] ; National Natural Science Foundation of China[U21B2038] ; National Natural Science Foundation of China[U23B2051] ; National Natural Science Foundation of China[62122075] ; Youth Innovation Promotion Association CAS ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDB0680201]
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Artificial Intelligence ; Computer Science, Information Systems ; Engineering, Electrical & Electronic
WOS记录号	WOS:001589873500025
出版者	IEEE COMPUTER SOC
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/41661
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Xu, Qianqian; Huang, Qingming
作者单位	1.Chinese Acad Sci, Inst Informat Engn, State Key Lab Informat Secur SKLOIS, Beijing 100045, Peoples R China 2.Univ Chinese Acad Sci, Sch Cyber Secur, Beijing 101408, Peoples R China 3.Shanghai AI Lab, Shanghai 200231, Peoples R China 4.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China 5.Univ Chinese Acad Sci, Sch Comp Sci & Technol, Beijing 100049, Peoples R China 6.Alibaba Grp, Secur Dept, Hangzhou 311121, Peoples R China 7.Sun Yat Sen Univ, Sch Cyber Sci & Technol, Shenzhen Campus, Shenzhen 518107, Peoples R China 8.Univ Chinese Acad Sci, Sch Comp Sci & Technol, Key Lab Big Data Min & Knowledge Management BDKM, Beijing 101408, Peoples R China 9.Peng Cheng Lab, Shenzhen 518055, Peoples R China
推荐引用方式 GB/T 7714	Cao, Zongsheng,Xu, Qianqian,Yang, Zhiyong,et al. SAQE: Complex Logical Query Answering via Semantic-Aware Representation Learning[J]. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING,2025,37(11):6651-6665.
APA	Cao, Zongsheng,Xu, Qianqian,Yang, Zhiyong,He, Yuan,Cao, Xiaochun,&Huang, Qingming.(2025).SAQE: Complex Logical Query Answering via Semantic-Aware Representation Learning.IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING,37(11),6651-6665.
MLA	Cao, Zongsheng,et al."SAQE: Complex Logical Query Answering via Semantic-Aware Representation Learning".IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 37.11(2025):6651-6665.