Framework Design of Intelligent Career Recommendation System for Undergraduates
Wenbin Liu, Lei Niu, Jinhua Zhao · 2022
The development of artificial intelligence technology has proudly enhanced the quality of life and education of students. The outbreak of COVID-19 in early 2020 dealt a huge blow to the world economy and workplace environment, therefore planning a career path before graduation is a primary and core task for undergraduate students to succeed in this era. This paper introduces the framework design of an intelligent career recommendation system, which is based on the analysis of the required career ability and students’ individual ability to achieve accurate career recommendations.