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A Survey of Techniques for Constructing Chinese Knowledge Graphs and Their Applications

Author

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  • Tianxing Wu

    (School of Computer Science and Engineering, Southeast University, Nanjing 211189, China
    School of Computer Science and Engineering, Nanyang Technological University, Singapore 639798, Singapore)

  • Guilin Qi

    (School of Computer Science and Engineering, Southeast University, Nanjing 211189, China)

  • Cheng Li

    (School of Computer Science and Engineering, Southeast University, Nanjing 211189, China)

  • Meng Wang

    (School of Computer Science and Engineering, Southeast University, Nanjing 211189, China)

Abstract

With the continuous development of intelligent technologies, knowledge graph, the backbone of artificial intelligence, has attracted much attention from both academic and industrial communities due to its powerful capability of knowledge representation and reasoning. In recent years, knowledge graph has been widely applied in different kinds of applications, such as semantic search, question answering, knowledge management and so on. Techniques for building Chinese knowledge graphs are also developing rapidly and different Chinese knowledge graphs have been constructed to support various applications. Under the background of the “ One Belt One Road (OBOR) ” initiative, cooperating with the countries along OBOR on studying knowledge graph techniques and applications will greatly promote the development of artificial intelligence. At the same time, the accumulated experience of China in developing knowledge graphs is also a good reference to develop non-English knowledge graphs. In this paper, we aim to introduce the techniques of constructing Chinese knowledge graphs and their applications, as well as analyse the impact of knowledge graph on OBOR. We first describe the background of OBOR, and then introduce the concept and development history of knowledge graph and typical Chinese knowledge graphs. Afterwards, we present the details of techniques for constructing Chinese knowledge graphs, and demonstrate several applications of Chinese knowledge graphs. Finally, we list some examples to explain the potential impacts of knowledge graph on OBOR.

Suggested Citation

  • Tianxing Wu & Guilin Qi & Cheng Li & Meng Wang, 2018. "A Survey of Techniques for Constructing Chinese Knowledge Graphs and Their Applications," Sustainability, MDPI, vol. 10(9), pages 1-26, September.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:9:p:3245-:d:169133
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    References listed on IDEAS

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    1. Christian Bizer & Tom Heath & Tim Berners-Lee, 2009. "Linked Data - The Story So Far," International Journal on Semantic Web and Information Systems (IJSWIS), IGI Global, vol. 5(3), pages 1-22, July.
    2. Tianxing Wu & Guilin Qi & Bin Luo & Lei Zhang & Haofen Wang, 2019. "Language-Independent Type Inference of the Instances from Multilingual Wikipedia," International Journal on Semantic Web and Information Systems (IJSWIS), IGI Global, vol. 15(2), pages 22-46, April.
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    Cited by:

    1. Chunyang Pan & William X. Wei & Etayankara Muralidharan & Jia Liao & Bernadette Andreosso-O’Callaghan, 2020. "Does China’s Outward Direct Investment Improve the Institutional Quality of the Belt and Road Countries?," Sustainability, MDPI, vol. 12(1), pages 1-21, January.
    2. Xuan Guo & Haizhong Qian & Fang Wu & Junnan Liu, 2021. "A Method for Constructing Geographical Knowledge Graph from Multisource Data," Sustainability, MDPI, vol. 13(19), pages 1-17, September.
    3. Junnan Liu & Haiyan Liu & Xiaohui Chen & Xuan Guo & Qingbo Zhao & Jia Li & Lei Kang & Jianxiang Liu, 2021. "A Heterogeneous Geospatial Data Retrieval Method Using Knowledge Graph," Sustainability, MDPI, vol. 13(4), pages 1-21, February.

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