Construction of Logistics Competitiveness System and Level Measurement of Node Cities of China Railway Express Based on Text Mining

This study constructs an initial selection of logistics competitiveness indicators from four dimensions: logistics scale, logistics resources, economic development, and green innovation.Based on the grey relational and redundancy models, the final indicator system is derived.In addition, text mining technology is used to extract high-frequency words from policy texts, and dimension keywords are mined using the Ochiia coefficient.Finally, a composite index algorithm is applied to calculate the weights of dimensions and indicators.The logistics competitiveness levels of the node cities of the China-Europe Railway Express from 2021 to 2023 are calculated, and the influencing factors and urban development potential are explored.This study not only provides a quantitative model for evaluating logistics competitiveness but also demonstrates the key role of data analysis and processing in the logistics field, highlighting the importance of data mining in identifying potential trends and optimizing decision-making.