情态动词
计算机科学
知识图
图形
互联网
数据科学
问题陈述
情报检索
人工智能
理论计算机科学
数据挖掘
万维网
工程类
管理科学
化学
高分子化学
作者
Jinghui Peng,Xinyu Hu,Wenbo Huang,Jian Yang
标识
DOI:10.1016/j.bdr.2023.100380
摘要
With the explosive growth of multi-modal information on the Internet, the multi-modal knowledge graph (MMKG) has become an important research topic in knowledge graphs to meet the needs of data management and application. Most research on MMKG has taken image-text data as the research object and used the multi-modal deep learning approach to process multi-modal data. In comparison, the structure of the MMKG is no uniform statement. This paper focuses on MMKG, introduces the related theories of multi-modal knowledge, and analyzes several common ideas about its construction. The survey also explains the structural evolution, proposes mirror node alignment to represent cross-modal knowledge for MMKG, lists some tasks' difficulties, and ultimately gives a sample MMKG for the news scene.
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