Personalized Recommendation Technology Research For Public Employment Services

At the present stage,the contradiction between the supply and demand of job seekers and employers in the field of public employment service is becoming more and more intense,and the voiceofrecruitment difficulties and employmentdifficulties is rising.With the development of Internet,computer technology andmobile phone terminal,the application of Internet platform,people are no longer satisfied in the form of passive query keywords to search through mobile or fixed terminal,but to all areas of service providers to be able to move through the fixed terminal initiative to provide users with all kinds of personalized application services meet the requirements that are more suitable for the actual needs.In this case,we choose a personalized recommendation system to apply the recommendation service to job seekers in the career introduction business.The use of personalized recommendation technology enables job seekers is to find the employment resources they need accurately and quickly.Personalized recommendation can be used effectively in the field of public employment service,especially in the career introduction business.It can not only provide convenience for both job seekers and employers.And the job seekers can get their own jobs more easily,which is very important to solve the problem of employment difficulties.This article will analyze the recommendation technology and introduce their respective advantages and disadvantages with the application cases in our actual work.According to the personalized recommendation algorithm,it is necessary to face the specific situation of different application scenes in the professional introduction business and the practical application of the personalized recommendation according to the different classification and the suitable scene.In order to make the job seeker more satisfied with the recommendation results in the business work,the traditional cooperative over rate recommendation algorithm is improved in technical aspects,and an algorithm that can adapt to the application needs and improve the accuracy of the recommendation is proposed.The following research and experiment are done:(1)according to the defects of the personalized recommendation algorithm and the specific situation of the different application scenes in the professional introduction business,the detailed analysis and analysis of the recommendation technology.(2)substituting employment application data to the neighborhood based recommendation algorithm,and improving the traditional algorithm according to the recommendation results.(3)in order to solve the practical needs of higher recommendation accuracy in the recommended jobs,the traditional recommendation algorithm is further improved,and a multidimensional recommendation algorithm has been developed to improve the accuracy of recommendation.Through the actual business data to achieve,through comparative analysis,the algorithm for job seekers recommended employment accuracy has greatly improved.It can be applied to the conclusion of application scenarios that need to provide accurate job recommendation for job seekers.