College Student Employment Management Recommendation System Based on Decision Tree Algorithm

With the continuous expansion of colleges and universities, the number of graduates continues to grow, and both students and the society will face huge employment pressure. The purpose of this paper is to design a recommendation system for college student employment management based on decision tree algorithm. A simple employment recommendation system is developed under Windows using Django architecture. Determine the research significance of employment recommendation for college graduates, then introduce the current development of recommendation systems and the research status of employment recommendation, and finally introduce mature application examples of user portraits. This paper introduces the application and implementation of ID3 algorithm in the employment analysis system of colleges and universities, including the process of building a decision tree, and then uses the generated decision tree to generate corresponding classification rules, obtains an employment prediction model, and uses the information of fresh students in the School of Computer Science and Engineering to predict employment. The model is tested, thereby realizing the prediction of the employment level of fresh graduates. There are 45 graduates whose employment status is in large-scale enterprises. The student employment recommendation system has been implemented, and the employment recommendation algorithm has been successfully applied to the employment recommendation work of the school's students.