The railway data service platform is deployed and applied in the main data center of Wuqing, which successively carries the data collection of intelligent Beijing zhang, transportation safety, cost reduction and efficiency improvement, and gathers a large number of structured data and unstructured data such as pictures and texts. In order to meet the needs of professional data analysis and application in complex scenarios, the railway data service platform uses various storage components including HDFS, Hive, PostgreSQL and so on. It is difficult to query data among various data storage components, it is difficult to carry out data association analysis among different data types, and the potential value of data has not been fully explored. Based on this, according to the urgent demand of current railway data service, this topic carries out the research of cross-modal data retrieval technology, puts forward the key technology of railway cross-modal data intelligent retrieval, sets up the typical application scenarios of graphic retrieval of railway accident faults. The combination of theoretical research and practical application, combined with the characteristics of the field of railway theory and method innovation, to provide technical support for the function upgrading of the railway data service platform.


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    Titel :

    Text Retrieval Technology and Platform Implementation of Railway Accident Fault


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Liu, Jun (Herausgeber:in) / Yang, Jianjian (Herausgeber:in) / Xu, Minyi (Herausgeber:in) / Yu, Quan (Herausgeber:in) / Shen, Wenchao (Herausgeber:in) / Sun, Zihan (Autor:in) / Xiang, Yimeng (Autor:in) / Yu, Ziyue (Autor:in) / Jin, Dian (Autor:in) / Sun, Shaozhen (Autor:in)

    Kongress:

    International Conference on Artificial Intelligence and Autonomous Transportation ; 2024 ; Beijing, China December 06, 2024 - December 08, 2024



    Erscheinungsdatum :

    28.03.2025


    Format / Umfang :

    9 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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