A Survey on Multimodal Knowledge Graphs: Construction, Completion and Applications

Yong Chen, Xinkai Ge (), Shengli Yang, Linmei Hu (), Jie Li and Jinwen Zhang
Additional contact information
Yong Chen: School of Computer Science and Technology, University of Science and Technology of China, Hefei 230052, China
Xinkai Ge: The Institute of Computer Science, Beijing University of Posts and Telecommunications, Beijing 100876, China
Shengli Yang: National Security School, China People’s Liberation Army National Defence University, Beijing 100091, China
Linmei Hu: School of Computer Science, Beijing Institute of Technology, Beijing 100811, China
Jie Li: The Institute of Computer Science, Beijing University of Posts and Telecommunications, Beijing 100876, China
Jinwen Zhang: North Automatic Control Technology Institute, Taiyuan 030006, China

Mathematics, 2023, vol. 11, issue 8, 1-27

Abstract: As an essential part of artificial intelligence, a knowledge graph describes the real-world entities, concepts and their various semantic relationships in a structured way and has been gradually popularized in a variety practical scenarios. The majority of existing knowledge graphs mainly concentrate on organizing and managing textual knowledge in a structured representation, while paying little attention to the multimodal resources (e.g., pictures and videos), which can serve as the foundation for the machine perception of a real-world data scenario. To this end, in this survey, we comprehensively review the related advances of multimodal knowledge graphs, covering multimodal knowledge graph construction, completion and typical applications. For construction, we outline the methods of named entity recognition, relation extraction and event extraction. For completion, we discuss the multimodal knowledge graph representation learning and entity linking. Finally, the mainstream applications of multimodal knowledge graphs in miscellaneous domains are summarized.

Keywords: multimodal knowledge graph; knowledge graph construction; knowledge graph completion; multimodal knowledge graph application (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2227-7390/11/8/1815/pdf (application/pdf)
https://www.mdpi.com/2227-7390/11/8/1815/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:11:y:2023:i:8:p:1815-:d:1120942

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().