计算机工程与应用2025，Vol.61Issue(6)：36-52,17.DOI:10.3778/j.issn.1002-8331.2408-0280
深度学习在知识图谱构建及推理中的应用
Applications of Deep Learning in Knowledge Graph Construction and Reasoning
摘要
Abstract
Knowledge graphs,as a structured form of knowledge representation in the field of natural language processing,can describe concepts and their relationships in the real world,and is often used in information retrieval,data manage-ment,and other fields.Deep learning has gradually become an emerging research hotspot due to its ability to automatically learn the underlying patterns and hierarchical representations from diverse data,which can be used for precise construc-tion and effective reasoning of large-scale,high-quality knowledge graphs.To further promote the technological integra-tion of deep learning and knowledge graphs,this paper focuses on the construction and reasoning processes of knowledge graphs,providing a comprehensive introduction to the relevant theories and latest research achievements in the fields of knowledge representation,knowledge extraction,knowledge fusion,and knowledge reasoning using deep learning.At the same time,according to the research trend in recent years,the paper highlights and summarizes the latest research results on the integration of graph deep learning and knowledge reasoning applicable to graph data feature inference.Finally,an overview and technical outlook are made on the integration and development of deep learning and knowledge graphs,providing reference and ideas for future research directions.关键词
知识图谱/深度学习/知识图谱构建/知识推理/图深度学习Key words
knowledge graph/deep learning/knowledge graph construction/knowledge reasoning/graph deep learning分类
计算机与自动化引用本文复制引用
孙宇,刘川,周扬..深度学习在知识图谱构建及推理中的应用[J].计算机工程与应用,2025,61(6):36-52,17.基金项目
教育部人文社会科学研究一般项目(22YJAZH165). （22YJAZH165）
