Design And Research Of College Students' Consumption Behavior Analysis System Based On Data Mining Technology

In recent years,more and more universities have begun to focus on smart campus construction.During the construction process,a large amount of data has been generated,including student information data in the student management system,book loan data in the library management system,and online data for students in the computer room Among them,in the college campus card system,the effective results of data mining analysis of consumption pipeline data with college students as the main body have important theoretical and practical significance for the management decision-making of college managers,because the consumption pipeline data is hidden behind The trajectory of students' behavior,and how to mine and use effective results in these campus data becomes the key issue.The campus card user behavior analysis system can effectively improve the school's information management level.By mining the consumption data in the campus card,it is helpful to analyze the trajectory of students' dining consumption behavior and provide data basis for the classification of poor students.This article takes the undergraduate student card consumption pipeline data as a data source for a period of time in a university to design a data mining system that can continuously process the student consumption pipeline data.The research content of this thesis has the following four points:First,in-depth study of the current status of domestic and international research on student campus card consumption behavior and the current status of cluster correlation analysis algorithms at home and abroad,sum up and learn from data mining related methods and theories.Second,elaborate the related concepts of data mining technology,and analyze the data mining foundation of student campus card swiping behavior.Third,according to the requirements of software engineering,the system needs to be analyzed,and the analysis system for mining students' consumption flow is designed,including functional structure design,process design,and mining model design.The system functional module design includes login function module and data preprocessing function.Modules,clustering function modules and association rule analysis function modules,and the design of the system database.Research on the core algorithms of the system,including K-means algorithm and FP-growth algorithm,and elaborate on the characteristics and advantages of their respective optimization algorithms to better analyze student consumption flow data.Fourth,design a college student consumption behavior analysis system based on data mining technology,use student main body consumption data to conduct experiments,and analyze the consumption patterns of various consumer groups hidden behind the data.The equivalence class division method and boundary value method were used to test the system to verify the effectiveness of the system.The study applies student consumption data to student consumption behavior analysis system,and the analysis results are helpful for the management and decision-making of college administrators and decision makers.Also laid a solid foundation for early warning and monitoring students' behavior trajectory.