Affiliations: [a]
Capital University of Economics and Business, Beijing, China
| [b]
Henan University of Economics and Law, Zhengzhou, Henan, China
Correspondence:
[*]
Corresponding author. Zhaokun Huang, Capital University of Economics and Business, Beijing, China. E-mail: [email protected].
Abstract: The fundamental solution to the problems of college students’ employment is to encourage college students to start their own businesses. Only by using entrepreneurship to promote employment can the real solution of China’s higher education employment problems be truly solved. Aiming at the current situation of college students’ entrepreneurship and employment, this paper builds a model system suitable for college students’ employment and entrepreneurship forecast and guidance through artificial intelligence algorithms and fuzzy logic models. The diversity-enhanced employment recommendation system developed in this paper uses the MVC three-tier architecture. Moreover, the diversity-enhanced employment recommendation system designed in this paper provides two recommendation methods: individual diversity optimization and overall diversity optimization, which takes into account the relationship between students’ personal interests and employment work. In addition, the system uses the basic idea of user-based collaborative filtering. Finally, this paper designs a control experiment to analyze the performance of this research model. The research shows that the entrepreneurship employment forecast and guidance model constructed in this paper has a certain effect.
Keywords: Artificial intelligence, fuzzy logic, college student employment, entrepreneurship, model
