Research And Implementation Of Human-Job Match System Based On Intelligent Recommendation Model

In recent years, in the domestic and international economic situation is becoming more and more serious background, with the number of college graduates in Beijing continued to increase, the problem of difficult employment of graduates highlights. However, in the process of applying for a job, graduates will not only face the objective situation, but also face huge employment information. These problems have greatly reduced the energy consumption, improve the cost, reduce the success rate of job seekers.Based on the actual situation of college graduates’ job hunting in Beijing and the characteristics of employing units, this paper designs a model of Intelligent Recommendation System Based on intelligent recommendation model. The intelligent recommendation model of the system is based on the combination of analytic hierarchy process model and SimRank algorithm model. Through the analytic hierarchy process model for graduates and employers released jobs were hard to find, index, two; matching through the "SimRank model" calculation of fresh graduates and graduates of the class, combined with the previous graduates of the contract unit, find graduates with potential contact unit based on the above two; contact calculation and get the recommended results. The system is verified by the actual data of a university, which has a higher recommendation accuracy than the other recommendation system.This system mainly includes six functions:login management, resume management, job evaluation, recruitment management, employment unit management and unit recommendation. System based on J2EE and Andriod technology development, can be deployed to the web platform and mobile terminal. The realization of this system can largely avoid the blindness of the graduates’ job hunting, and it has good application value and practical significance for the graduates and employers.