Research on Ship Relation Graph Analysis Driven by Multi-source Data
Hui Wan, Yingjie Xiao, Jianshun Mo, Yi Yu, Huaguang Li · 2021
In order to improve the application level of maritime supervision and maritime security data, This paper uses scientific knowledge graphs and big data analysis technology to integrate a large number of multi-source, heterogeneous, isolated maritime business and navigation service data for knowledge fusion and knowledge reasoning, and builds a multi-source data-driven ship relationship graph network to make ship data easier to be understood and processed by people and machines, and achieves more accurate and efficient maritime and navigation ship information intelligent retrieval, ship relationship portrait analysis, and visualization and other fusion applications, effectively improve the level of maritime data application and enhance the ability of maritime supervision and analysis decision-making for ship safety.