Research Article
Research on Text Recognition System of Logistics Enterprise Policy Based on Text Mining
@INPROCEEDINGS{10.4108/eai.6-1-2023.2330301, author={Jiahui Wang and Yidi Wang and Limei Xu}, title={Research on Text Recognition System of Logistics Enterprise Policy Based on Text Mining}, proceedings={Proceedings of the 2nd International Conference on Big Data Economy and Digital Management, BDEDM 2023, January 6-8, 2023, Changsha, China}, publisher={EAI}, proceedings_a={BDEDM}, year={2023}, month={6}, keywords={text mining logistics policy analysis system}, doi={10.4108/eai.6-1-2023.2330301} }- Jiahui Wang
Yidi Wang
Limei Xu
Year: 2023
Research on Text Recognition System of Logistics Enterprise Policy Based on Text Mining
BDEDM
EAI
DOI: 10.4108/eai.6-1-2023.2330301
Abstract
Modern logistics is an important support to realize the reform of supply side structure and the high quality development of economy. The Chinese government has also formulated a large number of policies to ensure the good and orderly development of logistics. Logistics enterprises concerned about the government policy can grasp the industry wind direction, good business decisions. However, logistics industry is a complex industry, with a wide range of policies, a large number of policies and complex contents. Therefore, enterprises are prone to omissions or inadequate grasp of key fields in practice. Therefore, this paper designs a policy text recognition system for logistics enterprises based on text mining. TF-IDF algorithm is used to extract the feature words of policy texts, and random forest is used to classify policy texts. The results are compared with manual labeling results to calculate the accuracy and recall rate. Through experiments, it is found that random forest algorithm has a high accuracy rate of policy text recognition. Logistics enterprises can use random forest algorithm to identify and analyze policy text, so as to improve the working efficiency and decision-making accuracy of logistics enterprises.
