Analysis And Application Of Campus Card Consumption Data Based On Data Mining

Universities are paying more and more attention to IT construction.Many colleges and universities have set up their peculiar information construction standards for their own information platforms,and realized data sharing.However,in the process of information construction,effective use of mass data gathered by the platforms are ignored by the universities and colleges.In th e perspective of student management,how to make use of the data collected by the established educational administration and teaching management system,campus card management system,library and documents management system and other systems,and tap the potential of such systems,and better the service to student management divisions and help them to identify students suffering economic hardship is an important research subject.This thesis based on the consumption list of campus cards used in a Wuhan-based university,an in-depth study of the Clustering Algorithm k-means and the Decision Tree Algorithm C4.5 used in data mining were performed before exchanging data with relevant database by the data switching tool of kettle,thus forming the dataset to be analyzed.Then the k-means algorithm was used to perform clustering for consumption data of the campus cards of all students in the university,in the aim of identifying the consumption features of poverty-stricken students.And then such features,togeth er with academic performance of the poverty-stricken students,were used to create the evaluation model of poverty-stricken students after creating decision-making and analysis samples of library borrowing data and basic information of the poverty-stricken students.C4.5 algorithm was used to on the weka platform to test the accuracy of the evaluation model of poverty-stricken students,and to offer good suggestion to relevant departments of the university.