Research And Application Of Student Employment Recommendation Platform Based On Hadoop Ecological Technology

With the continuous popularization of education in our country,the number of graduates in our country continues to increase.In order to reduce employment pressure,employment recommendation research has become a key field.The core issue is how to find jobs that match individual abilities to reduce the employment pressure of job seekers.And help them effectively find jobs that fit their abilities.Therefore,in order to solve this problem,this topic designs and implements an employment recommendation system.Based on the background of big data,this paper analyzes and designs a personalized employment recommendation platform based on offline analysis and real-time recommendation on the basis of Hadoop,Spark,Flume and other big data technologies and related recommendation algorithms.In the recommendation algorithm,the collaborative filtering algorithm is used as the core,and the collaborative filtering algorithm is optimized by introducing user portraits and constructing user capability labels,so that it can achieve the best matching state,thereby reducing the cold start problem of new users.In the offline analysis module,ALS is used as the training implicit semantic model of the collaborative filtering algorithm,and the optimal parameter combination is found through continuous parameter adjustment,so as to calculate the ideal RMSE and MAE.In order to further reduce the cold start problem of new users,when new users are introduced into the recommendation system to log in,they need to choose the type of job they are interested in to solve.Finally,on the basis of combining technical theory and recommended algorithm research,according to the idea of software engineering design,the platform’s requirements and feasibility are analyzed,and the platform’s feasibility is clarified.At the end of this paper,using Spring Boot as the development technology,based on the Spark distributed computing framework,combined with Kafka,Flume,Mongo DB and other related big data technologies,the employment recommendation platform was realized and completed,and the platform was tested to ensure the operability of the platform.By using big data framework components as the basis,the stability of the platform and the accuracy of information recommendation can be effectively improved in the case of a large amount of data.