IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i7p3209-d1627958.html
   My bibliography  Save this article

Architecture and Application of Mine Ventilation System Safety Knowledge Graph Based on Neo4j

Author

Listed:
  • Keping Zhou

    (School of Resources and Safety Engineering, Central South University, Changsha 410083, China)

  • Xiaohui Lu

    (School of Resources and Safety Engineering, Central South University, Changsha 410083, China)

  • Chun Yang

    (School of Resources and Safety Engineering, Central South University, Changsha 410083, China)

  • Zhiqing Chen

    (Guangxi Fozi Mining Co., Ltd., Wuzhou 543100, China)

  • Wei Liu

    (Guangxi Fozi Mining Co., Ltd., Wuzhou 543100, China)

  • Haiwen Yan

    (Guangxi Fozi Mining Co., Ltd., Wuzhou 543100, China)

Abstract

To improve the safety management and accident prevention capabilities of mine ventilation systems, the application of knowledge graph technology is proposed. By employing methodologies such as data analysis, entity relationship definition, and entity relationship extraction, and entity extraction using BERT + BiLSTM + CRF model, a safety knowledge graph for the mine ventilation system is constructed. This facilitates the structured processing of historical accident-related textual data and enables the visual analysis and application of accidents based on the knowledge graph. The research results demonstrate that knowledge graph technology can effectively integrate unstructured data and present it in visual graphs or tables. By utilizing Cypher query statements, multi-dimensional accident statistics and the frequency analysis of specific information can be generated, contributing to a comprehensive understanding of accident occurrence patterns. Leveraging the node-to-node characteristics of the knowledge graph, a correlation analysis between entities is conducted, deeply exploring relationships among different types of data, thereby providing new insights to prevent accidents in mine ventilation systems. Moreover, the analysis of mine ventilation accidents and system failure characteristics offers valuable guidance for the safety management of mine ventilation systems.

Suggested Citation

  • Keping Zhou & Xiaohui Lu & Chun Yang & Zhiqing Chen & Wei Liu & Haiwen Yan, 2025. "Architecture and Application of Mine Ventilation System Safety Knowledge Graph Based on Neo4j," Sustainability, MDPI, vol. 17(7), pages 1-18, April.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:7:p:3209-:d:1627958
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/7/3209/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/17/7/3209/
    Download Restriction: no
    ---><---

    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:17:y:2025:i:7:p:3209-:d:1627958. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.