Researeh And Application Of Personalized Recommendation Method In The Application Of College Entrance Examination

With the rapid development of educational and network technology,more and more new information technologies are applied in educational field.College entrance examination is an important test in one student's life,so that the voluntary report after this examination becomes especially important.Personalized recommendation system is a system that can recommend information accurately for students in a large amount of information according to the preferences of them,and it is widely used at present.It can also be used in individualized recommendation when students can not choose suitable volunteers quickly because of the complexity and diversity of college and specialty information.This kind of individualized recommendation is a kind of recommendation method,which has good practical significance.In this paper,two new recommendation algorithms are proposed:one is the recommendation algorithm of individualized university recommendation report system,the other is the recommendation algorithm of individualized enrollment advertisement based on examinee data.The main work of this paper includes the following aspects.(1)In this paper,the trend and present situation of the reform of the college entrance examination enrollment system has been introduced,at the meantime analyzes the deficiency of the individualized recommendation function of App in the national college entrance examination,and puts forward an algorithm to generate the recommendation report based on the prediction of the pitch score in colleges and universities.The algorithm is verified and studied by two indexes: the accuracy rate and the total pushing rate.The accurate rate is the accuracy rate of the university recommended by the algorithm.According to the rank of the examinee who can go to the university in the recommendation report,the pushing rate is the ratio of the total number of colleges and universities that the examinee can go on in the recommendation report and the total number of colleges and universities that the examinee can actually go on.This paper studies and proves the algorithm by calculating the accuracy rate and the total pushing rate of all the scores above a provincial control line in Jiangxi province in 2016.(2)Collecting the behavior data of examinee users who use App to simulate thefilling process,and put forward the recommendation algorithm of individualized enrollment advertisement.Collecting the behavior data of the examinee in the process of using App simulation to fill in,including the selected major and the province of the selected university,based on which to model the user,and at the same time,carry on the advertisement recommendation to the user through the simulation advertisement data.And through the calculation of the recommended advertising and user correlation verification algorithm.(3)Detail introduction of the implementation of App server and client.For the service side given the key codes and implementation process of the data,logic and control layer,for the client side given the storage of data and logic control method.