Study On Express Industry Based On Data Mining And Visualization

Chinese society is undergoing rapid development and changes:transportation infrastructure is becoming more and more perfect,the mobile Internet becomes a new infrastructure,e-commerce has sprung up,and online shopping has become a new choice in daily life.These changes have pushed express delivery industry into a golden age of development.In this paper express delivery industry is analyzed from the perspective of customers,because customers are the key service objects in this industry,and customer requirements drive express delivery industry to develop in the direction of intelligence,efficiency,and refinement.The customer satisfaction of express delivery services directly reflects current development level of this industry.At this stage,express delivery companies can mine users’ potential needs through customer satisfaction investigation,which can effectively improve their deficiencies,enhance corporate competitiveness,and drive corporate innovation and development.An indicator system of customer requirements on express industry is constructed,referring to Bain’s B2B elements of value model and the Censydiam user motivation analysis model.Keywords of express industry service models and new technology applications are extracted,and the development status of express industry is analyzed.In terms of customer satisfaction,referring to the SERVQUAL model,the LSQ model and the national standard of express service in China,an index of user satisfaction on express industry is constructed.By using open big data on Internet and new technologies in the field of data mining and natural language processing,customer requirements and user satisfaction in express delivery industry are mined and visualized.Relevant data is obtained including six well-known domestic express companies:EMS,SF Express,Shentong,Zhongtong,Yuantong and Yunda,from Black Cat Dispute Resolution Platform,news from express companies’ official website,website data from State Post Bureau of China,Sina Weibo and other channels.Using keyword recognition,word clustering,semantic computing,sentiment analysis and other techniques,text data is analyzed,the indicator system of customer requirements and user satisfaction are verified.In conclusion,a method of express industry research based on data mining and visualization technology is realized in this paper.