IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v10y2018i9p3245-d169133.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/10/9/3245/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/10/9/3245/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. 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.
    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Stahl, Florian & Schomm, Fabian & Vossen, Gottfried, 2012. "Marketplaces for data: An initial survey," ERCIS Working Papers 14, University of Münster, European Research Center for Information Systems (ERCIS).
    2. Anett HOPPE & Ana ROXIN & Christophe NICOLLE, 2015. "Ontology-based Integration of Web Navigation for Dynamic User Profiling," Informatica Economica, Academy of Economic Studies - Bucharest, Romania, vol. 19(1), pages 10-24.
    3. Anne E Thessen & Cynthia Sims Parr, 2014. "Knowledge Extraction and Semantic Annotation of Text from the Encyclopedia of Life," PLOS ONE, Public Library of Science, vol. 9(3), pages 1-10, March.
    4. Kurt Sandkuhl & Hans-Georg Fill & Stijn Hoppenbrouwers & John Krogstie & Florian Matthes & Andreas Opdahl & Gerhard Schwabe & Ömer Uludag & Robert Winter, 2018. "From Expert Discipline to Common Practice: A Vision and Research Agenda for Extending the Reach of Enterprise Modeling," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 60(1), pages 69-80, February.
    5. Phillip Lord & Simon Cockell & Robert Stevens, 2012. "Three Steps to Heaven: Semantic Publishing in a Real World Workflow," Future Internet, MDPI, vol. 4(4), pages 1-12, November.
    6. Marta Sabou & Irem Onder & Adrian M. P. Brasoveanu & Arno Scharl, 2016. "Towards cross-domain data analytics in tourism: a linked data based approach," Information Technology & Tourism, Springer, vol. 16(1), pages 71-101, March.
    7. Wuhui Chen & Incheon Paik, 2013. "Improving efficiency of service discovery using Linked data-based service publication," Information Systems Frontiers, Springer, vol. 15(4), pages 613-625, September.
    8. Nitesh Khilwani & J. A. Harding, 2016. "Managing corporate memory on the semantic web," Journal of Intelligent Manufacturing, Springer, vol. 27(1), pages 101-118, February.
    9. Veale, Michael & Binns, Reuben, 2017. "Fairer machine learning in the real world: Mitigating discrimination without collecting sensitive data," SocArXiv ustxg, Center for Open Science.
    10. Schiavone, Francesco & Paolone, Francesco & Mancini, Daniela, 2019. "Business model innovation for urban smartization," Technological Forecasting and Social Change, Elsevier, vol. 142(C), pages 210-219.
    11. Ghadeer Ashour & Ahmed Al-Dubai & Imed Romdhani & Daniyal Alghazzawi, 2022. "Ontology-Based Linked Data to Support Decision-Making within Universities," Mathematics, MDPI, vol. 10(17), pages 1-21, September.
    12. E. G. Stephan & T. O. Elsethagen & L. K. Berg & M. C. Macduff & P. R. Paulson & W. J. Shaw & C. Sivaraman & W. P. Smith & A. Wynne, 2016. "Semantic catalog of things, services, and data to support a wind data management facility," Information Systems Frontiers, Springer, vol. 18(4), pages 679-691, August.
    13. Hossein Hassani & Xu Huang & Mansi Ghodsi, 2018. "Big Data and Causality," Annals of Data Science, Springer, vol. 5(2), pages 133-156, June.
    14. Muhammad Sajid Qureshi & Ali Daud, 2021. "Fine-grained academic rankings: mapping affiliation of the influential researchers with the top ranked HEIs," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(10), pages 8331-8361, October.
    15. Sean Kennedy & Owen Molloy & Robert Stewart & Paul Jacob & Maria Maleshkova & Frank Doheny, 2012. "A Semantically Automated Protocol Adapter for Mapping SOAP Web Services to RESTful HTTP Format to Enable the Web Infrastructure, Enhance Web Service Interoperability and Ease Web Service Migration," Future Internet, MDPI, vol. 4(2), pages 1-24, April.
    16. Simon French, 2012. "Expert Judgment, Meta-analysis, and Participatory Risk Analysis," Decision Analysis, INFORMS, vol. 9(2), pages 119-127, June.
    17. Costantino Thanos, 2017. "Research Data Reusability: Conceptual Foundations, Barriers and Enabling Technologies," Publications, MDPI, vol. 5(1), pages 1-19, January.
    18. Raymond Y. K. Lau & J. Leon Zhao & Wenping Zhang & Yi Cai & Eric W. T. Ngai, 2015. "Learning Context-Sensitive Domain Ontologies from Folksonomies: A Cognitively Motivated Method," INFORMS Journal on Computing, INFORMS, vol. 27(3), pages 561-578, August.
    19. Muhammad Ahtisham Aslam & Naif Radi Aljohani, 2017. "SPedia: A Central Hub for the Linked Open Data of Scientific Publications," International Journal on Semantic Web and Information Systems (IJSWIS), IGI Global, vol. 13(1), pages 128-147, January.
    20. Costantino Thanos, 2016. "A Vision for Open Cyber-Scholarly Infrastructures," Publications, MDPI, vol. 4(2), pages 1-18, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:10:y:2018:i:9:p:3245-:d:169133. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.