Research on the demand characteristics of logistics talents based on Web text mining

Abstract

In view of the coexistence of “difficulty in employment” for logistics job seekers and “difficulty in recruitment” for enterprises, this work uses web crawler technology to collect a total of 17,086 pieces of data from recruitment websites, and uses web text mining to segment Chinese recruitment data text, using BERT pre-training depth model Process text clustering and sentiment analysis for unstructured information, and use complex network tools to visually interpret the relationship between job and demand characteristics. The analysis results provide professional development help for logistics talents, so that colleges and universities can provide specific suggestions for transporting outstanding logistics talents to enterprises through the market demand more clearly on the training direction of students.