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

Author

Listed:
  • 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)

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.

Suggested Citation

  • Yong Chen & Xinkai Ge & Shengli Yang & Linmei Hu & Jie Li & Jinwen Zhang, 2023. "A Survey on Multimodal Knowledge Graphs: Construction, Completion and Applications," Mathematics, MDPI, vol. 11(8), pages 1-27, April.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:8:p:1815-:d:1120942
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    Cited by:

    1. Ping Lou & Dan Yu & Xuemei Jiang & Jiwei Hu & Yuhang Zeng & Chuannian Fan, 2023. "Knowledge Graph Construction Based on a Joint Model for Equipment Maintenance," Mathematics, MDPI, vol. 11(17), pages 1-23, August.

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