Optimization of Information System based on Random Sampling Data Clustering Marketing

Abstract

Optimization of the customer relationship management information system based on random sampling data clustering and its integration in intelligent marketing is studied in the paper. For the design of the system, start Tomcat through the built-in server in MyEclipse to realize B/S interactive mode. The access mechanism of the system adopts the Application that can save the common data information of all users. The SSH framework has advantages and can improve the efficiency of enterprise production management, but with the widespread use of this model, the defects of the three frameworks have gradually emerged: Struts makes the system structure clearer, but also increases the system complexity. Therefore, the proposed model is applied into the discussion on the customer relationship management information system. The efficient random sampling data clustering algorithm is designed for performing a comprehensive analysis. Through testing, the results are proven.