This research utilizes higher-order dependency relationships for the modeling of higher-order dependency networks from voluminous maritime flow data and introduces higher-order dependency mining to uncover critical port information in the China-Southeast Asia region as well as the coopetition relationships between ports. Analysis of maritime data from the years 2018 and 2023 indicates that global ports maintain stability and competitiveness through their evolution, with Singapore serving as the central hub connecting China and Southeast Asia. Subsequent analysis employing dependency paths indicates that in recent years, the dependency relationships among ports between China and Southeast Asia have achieved higher orders and greater complexity.


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    Title :

    Big Data Mining of Maritime Shipping Flows Based on Dependency Relationships


    Contributors:
    Fu, Yude (author) / Li, Xiang (author) / Lu, Xiongyi (author) / Yu, Mengjun (author) / Huangpeng, Qizi (author) / Duan, Xiaojun (author)


    Publication date :

    2024-04-19


    Size :

    2726345 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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