| After the entrance examination in 2020,Shandong Province issued the guidance on enrollment filling in and filling in the general colleges and universities in 2020,which describes a series of changes in voluntary filling and admission rules,marking the implementation of the new college entrance examination in Shandong Province.After the new policy was implemented,the rules of authority for voluntary setting and filling in volunteer have changed greatly.Among them,the biggest change is to cancel the liberal arts and Sciences Branch,and adopt the "3 + 3" model.At the same time,the mode of voluntary filling has changed from "college + specialty" to "specialty + College".The number of voluntary applicants can fill in has increased from 36 to96.The impact of policy changes includes the drastic fluctuation of the number of voluntary admission positions in 2020,which has led to a sharp decline in the available reference admission data in previous years.In addition,the increase of the number of volunteers can be filled in,which makes it difficult for candidates to choose when facing a large amount of volunteer information,which causes the phenomena of "high scores low wish","recording not what they wish".A survey by Peking University shows that one third of college students in Beijing are not interested in the major they study.In order to solve this situation,this paper analyzes the needs of examinee users in detail.Under the background of Shandong new policy of college entrance examination,a voluntary recommendation system for college entrance examination is designed,which not only meets the individual needs of candidates,but also considers the actual scores of candidates,and makes personalized recommendation for candidates.First of all,the admission scores of Shandong examinees in Colleges and universities across the country over the years are crawled from the network.By analyzing the change rules of the voluntary admission scores before and after the policy change,the line difference between the voluntary admission score line and the provincial control line is selected as the time series variable,and the grey prediction model is used to predict the admission scores of Shandong examinees in 2020 The experimental results show that the error of this method is more than twice smaller than that of the traditional method.After that,combined with the college entrance examination score and the predicted volunteer admission score,the admission probability of the volunteer to the candidate is obtained.Secondly,when making voluntary recommendation for examinees,it is based on examinee's score,supplemented by examinee's personalized needs.In order to meet the personalized needs of different candidates,in addition to the candidates' own more clear target college region,college level,campus environment and other personalized needs,the system also uses the personality test to help candidates clear their own unclear personalized needs.Because most of the candidates are senior high school graduates,the system lacks the candidates' history score of volunteering.In order to solve the problem of data sparsity and cold start in traditional recommendation system,this paper takes the content-based recommendation algorithm as the framework,integrates the constraint based recommendation method,and optimizes the weight of each personalized requirement attribute through genetic algorithm.Combining the admission probability of candidates with individual needs,a reasonable combination of volunteer distribution is generated,and the volunteer combination is recommended to candidates after a reasonable ranking.Finally,the system is developed by springboot,mybatis plus,Vue and other technologies.This system avoids the problems of unreasonable choice,unreasonable sorting and incomplete filling in 96 candidates,and provides a practical decision tool for candidates to make voluntary decision,which meets the needs of users. |
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