Abstract: In recent years, there has been a significant increase in the number of students trying to broaden the work opportunities available to college graduates. This study presents an intelligent employment management system that may be used in educational institutions for students to gain a better understanding of their occupations and analyzing the sectors in which they will work. In this article, the fundamental concepts of information recommendation are discussed, as well as a customized recommendation system for entrepreneurship that is provided. The fundamental information and personal interest points of college students are represented by feature vectors. These feature vectors provide positive theoretical support for the career planning and employment and entrepreneurship information suggestions of college students. In conclusion, an analysis of the performance of the proposed model is performed to provide college students with a system that is both convenient and quick in terms of information recommendation. This will result in an indirect improvement in the employment rate of graduates and will provide solutions that correspond to the problem of difficult employment.

Yiming Wang and Chi Che, “A Machine Learning-Based Intelligent Employment Management System by Extracting Relevant Features” International Journal of Advanced Computer Science and Applications(IJACSA), 15(12), 2024. http://dx.doi.org/10.14569/IJACSA.2024.0151235

@article{Wang2024,
title = {A Machine Learning-Based Intelligent Employment Management System by Extracting Relevant Features},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2024.0151235},
url = {http://dx.doi.org/10.14569/IJACSA.2024.0151235},
year = {2024},
publisher = {The Science and Information Organization},
volume = {15},
number = {12},
author = {Yiming Wang and Chi Che}
}