多模态知识图谱融合技术研究综述OA北大核心CSTPCD

Multi-modal knowledge graphs(MMKG)integrate various modal information such as vision and text,presenting knowledge structures graphically.With the advancement of artificial intelligence,MMKG have played a significant role in recommendation systems,intelligent Q&A,and knowledge search among other fields.Compared to traditional knowledge graphs,MMKG can understand and present knowledge in multiple dimensions,possessing superior representation and application capabilities.To delve deep into the study of MMKG,this review first conducts a detailed analysis and elucida-tion of the value and categories of MMKG.Based on different construction methods,it compares and summarizes multi-modal knowledge extraction,representation learning,entity alignment,and other aspects,categorizes multi-modal knowl-edge integration methods.It analyzes the progress in the applications of MMKG,discusses the limitations of MMKG,and proposes future research directions in the field of MMKG.