Design And Realization Of The College Entrance Eexamination Volunteer Intelligent Reporting System

Every year after the college entrance examination,parents and children are faced with a major decision about their children's fate,that is,the college entrance examination to fill in the voluntary.Therefore,how to guide parents and children how to volunteer,choose a suitable college major,is the current education industry needs to solve a problem.With the rapid development of computer information technology.At present,many companies have developed a voluntary filing system,But the existing filing system simply presents the paper version of the enrollment data to the volunteer filing system in a different way,Can Not solve examinee because fill in a voluntary blindly and cause the problem such as professional unfitness,high score low.This article takes Zhejiang Province as the research goal,analysis of the characteristics of voluntary entry for college entrance examination.This article uses artificial intelligence,personalized recommendation,data mining and other technologies to develop an efficient,convenient and practical intelligent volunteer reporting system.The specific content of this article includes the following aspects.First,according to the admission data of colleges and universities in the past three years,a prediction model based on BP neural network is used to predict the admissions of colleges and universities in that year.Secondly,obtain the candidate's preference information to construct the user's interest feature vector,use user-based collaborative filtering recommendation algorithm to make voluntary recommendations for users,however,due to the short development time of the system,the use of collaborative filtering recommendation algorithms has sparse data and cold start problems,and it is not possible to make voluntary recommendations for some users,for this part of the user system,a constraint-based filtering recommendation algorithm is used for voluntary recommendation.Moreover,according to the admission data of colleges and universities in previous years and the model based on BP neural network,the admission position of colleges and universities in the current year is predicted.Finally,the detailed analysis of the functional requirements of the college entrance examination voluntary intelligent reporting system,and then the overall system design,and detailed design of each functional module,then perform functional and performance tests on the college entrance examination voluntary intelligent reporting system.The test results show that the college entrance examination voluntary intelligent reporting system can realize functions such as predicting the admission position of colleges and universities in the current year,making voluntary recommendations to users,and predicting the probability that candidates will be accepted by a certain college.