Behavior Data Mining And Analysis System For Campus Big Data

With the rapid development of science and technology,human beings have produced countless data information in production and life.,and data has become a basic resource from the object of processing.Colleges and universities have accumulated a large number of student information and behavior data information,but it's hard for us to find it with an intuitive feeling,It must be expressed through data mining methods,and valuable information can be found to provide valuable reference for the rational allocation of university resources,campus planning and construction,and teacher and student management.In the process of design,this paper applies Hadoop big data processing system to realize the data acquisition and mining operation of campus card.First of all,this paper makes a brief analysis of the campus card data of colleges and universities and the current research status of related technologies.Then,the Hadoop technology commonly used in data mining is analyzed in detail,and the principle and process of FP-Growth algorithm are introduced in detail.Third,the user data warehouse of this kind of campus card is designed based on sqoop technology.Finally,the behavioral big data is analyzed and analyzed.The first,Statistical analysis determines the number of people dining in the cafeteria at different time periods,and analyzes the changes,thus clarifying the law related to the peak period of school meals;Second,through the statistics of part of the students' consumption,the decision tree algorithm is used to establish the student poverty model,and then the pruning method is optimized to improve the accuracy of the evaluation.Third,statistics the merchants that students often go to,mine and analyze the relevant data,determine the association rules between students and merchants,so as to get a more convenient way for students.