Intelligent College Entrance Examination Volunteer Recommendation System Based On Machine Learning

With the rapid development of the Internet and educational informatization,the application of personalized recommendation systems in the field of education has become more and more extensive.Filling in volunteers is an important part of the college entrance examination,but in the case of many colleges and majors,it is difficult for candidates to quickly obtain effective information and make personalized choices that suit them.This paper analyzes the individual needs of candidates and parents,and extracts valuable information from a large number of schools and professions.It is recommended to candidates and parents to help candidates fill in their volunteers.The system obtains the relevant data of each university from the major network platforms as the historical data in the college entrance examination volunteer text,and increases the Wikipedia data as an extension to train the word vector for the case of less characteristic words in the historical data.The traditional text representation method does not consider the semantics and the existence of dimensional disasters.The word2 vec is introduced into the content-based recomendation algorithm,which improves the existing semantic results of related website search results.At the same time,there are shortcomings in the existing related websites which only can be searched according to specific professions,and considering the phenomenon that the professional intentions of the candidates and parents are relatively free and colloquial.This paper will use cosine similarity and simple common words method.Text similarity calculation method is improved,thereby solving the problem that the candidate and the parent do not know the specific professional name of a certain major in the college.Then,the existing personalized recommendation system is optimized for the multi-attribute attributes in the historical data,such as the college level,school environment,professional level,and teacher strength.Finally,based on the optimization method proposed above,a college entrance examination recommendation system is designed and implemented.After experimental demonstration,the optimized system improves the retrieval function of existing related websites.