Knowledge Graph: A Survey

Abstract

Abiola Akinnubi and Jeremiah Ajiboye

This survey discusses the concept of knowledge graphs, including their construction, extraction, and applications. Various tools such as Zotero, Web of Science, Google Scholar, EndNote, and VosViewer are used to analyze and visualize collected data. A Boolean query mechanism ensures the gathered material is relevant to the study. The discussion includes studies on relation extraction using graph neural networks, the application of knowledge graphs in biomedical research, and the use of knowledge graph embedding in healthcare. These studies highlight the growing importance of knowledge graphs in managing and representing complex information. Notable studies discussed include the role of knowledge graphs in connecting related medical information, the application of knowledge graph technology in healthcare, and the potential benefits and limitations of using knowledge graph embedding in biomedical data analysis. This survey paper provides valuable insights into the growing importance of knowledge graphs in managing and representing complex information and how they can help provide new insights into various fields. It suggests potential future directions for research in this area, highlighting the importance of continued exploration and innovation to realize the potential of knowledge graphs fully.

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