Railway risk prevention has been an important task in railway operation. Accidents like derailment are severe problems for operation. Intelligent systems for safety management rely on existing knowledge heavily. Knowledge graph as a kind of knowledge management techniques is popular recently. For specific domains have unique dictionaries and rules, ontologies provide conceptual layers to help constructions of their knowledge graphs. This study proposes a methodology to build railway domain ontologies and constructs an ontology with derailment accident data as an example. Ontologies used to be built by terms, while railway terms need to be updated on time for actual scenarios. A method based on Pearson Correlation Coefficient has been taken as validation test of entities extraction and instances updating in proposed methodology. The constructed derailment accident ontology could provide the conceptual layer and basic structure for railway knowledge graph. And the ontology has achieved functions like knowledge retrival and knowledge visualization with the help of Protégé.


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    Title :

    Data-Driven Ontology Construction Method for Railway Derailment Accidents


    Additional title:

    Lect. Notes Electrical Eng.


    Contributors:
    Qin, Yong (editor) / Jia, Limin (editor) / Liang, Jianying (editor) / Liu, Zhigang (editor) / Diao, Lijun (editor) / An, Min (editor) / Zhao, Ruhao (author) / Ma, Xiaoping (author) / Dong, Honghui (author) / Yan, Han (author)

    Conference:

    International Conference on Electrical and Information Technologies for Rail Transportation ; 2021 October 21, 2021 - October 23, 2021



    Publication date :

    2022-02-23


    Size :

    10 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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