Design and Practice of Optimization Algorithm for College Career Planning Service Based on Cloud Computing Platform

Abstract

Career planning is an important part of higher education, and effective career planning can not only help college students clarify their career goals, but also provide them with paths to realize their career goals. The article designs a cloud computing-based career planning recommendation system for college students, adopting the three-layer architecture of cloud computing, combining the student information model, the career information model and the collaborative filtering recommendation algorithm with improved CVAE and CPMF to realize the accurate matching of student and career information. In this paper, an empirical study is carried out with students from five colleges and universities. In this study, the gender difference of college students as a group has a certain impact on career, and generally speaking, the level of career planning of male students is higher than that of female students. The part-time experience is also reflected in the internship experience or not, and this aspect is the main influence on the level of career planning. The practical results show that it is feasible to carry out the career planning service for colleges and universities based on cloud computing platform.