Application of SPSS Cluster Analysis in the Smart Promotion Strategies of Cross-border E-commerce in Informationized Textiles and Clothing with Artificial Intelligent Models

Abstract

This paper conducts the study on the application of SPSS cluster analysis in the smart promotion strategies of the cross-border E-commerce in the informationized textiles and clothing with artificial intelligent models. The team used literature survey methods, social survey methods, data processing methods (mainly analytic hierarchy process) and other research methods to visit a number of textile cross-border e-commerce companies in Wuhan and Shenzhen together with their instructors, and conducted questionnaire surveys. The team mainly used levels the analytical method processes the questionnaire data and names the target level as the cross-border e-commerce practitioner skills evaluation index system. The guidance layer is divided into four dimensions: operational planning capabilities, service capabilities, big data analysis capabilities, and innovation capabilities. With these factors, the data clustering algorithm is applied with the SPSS. At the beginning of the algorithm, the individual population particles are initialized according to the set parameters, then the dispersion operator is executed to change the position of the particle with the same coding structure as the current particle, and then the AI tools are used to optimize the system.

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