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A Tutorial and Survey on Fault Knowledge Graph

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Cyberspace Data and Intelligence, and Cyber-Living, Syndrome, and Health (CyberDI 2019, CyberLife 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1138))

Abstract

Knowledge Graph (KG) is a graph-based data structure that can display the relationship between a large number of semi-structured and unstructured data, and can efficiently and intelligently search for information that users need. KG has been widely used for many fields including finance, medical care, biological, education, journalism, smart search and other industries. With the increase in the application of Knowledge Graphs (KGs) in the field of failure, such as mechanical engineering, trains, power grids, equipment failures, etc. However, the summary of the system of fault KGs is relatively small. Therefore, this article provides a comprehensive tutorial and survey about the recent advances toward the construction of fault KG. Specifically, it will provide an overview of the fault KG and summarize the key techniques for building a KG to guide the construction of the KG in the fault domain. What’s more, it introduces some of the open source tools that can be used to build a KG process, enabling researchers and practitioners to quickly get started in this field. In addition, the article discusses the application of fault KG and the difficulties and challenges in constructing fault KG. Finally, the article looks forward to the future development of KG.

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Authors and Affiliations

  1. School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, 100083, China

    XiuQing Wang

  2. School of Reliability and Systems Engineering, Beihang University, Beijing, 100083, China

    ShunKun Yang

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  1. XiuQing Wang
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  1. University of Science and Technology, Beijing, China

    Huansheng Ning

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Wang, X., Yang, S. (2019). A Tutorial and Survey on Fault Knowledge Graph. In: Ning, H. (eds) Cyberspace Data and Intelligence, and Cyber-Living, Syndrome, and Health. CyberDI CyberLife 2019 2019. Communications in Computer and Information Science, vol 1138. Springer, Singapore. https://doi.org/10.1007/978-981-15-1925-3_19

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  • DOI: https://doi.org/10.1007/978-981-15-1925-3_19

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