Implementation and Application of Employment Recommendation System for College Students with Personalized Preferences

Author:

Guo Fang1,Li Zhiqiang2

Affiliation:

1. Department of Mechanical Engineering , Shanxi Institute of Technology , Yangquan , Shanxi , China .

2. Department of Civil Engineering , Shanxi Institute of Technology , Yangquan , Shanxi , China .

Abstract

Abstract With the popularization of higher education, the competition in the employment market of college students is becoming increasingly intense. To enhance the employment efficiency and satisfaction of college students. The study first analyzes college students’ employment unit selection, attribute preference, and location preference through an employment recommendation algorithm. The collaborative filtering algorithm is utilized to complete personalized modeling and output the final recommendation results based on the acquired employment preferences and relevant data collection. Finally, the gradient descent method is used to evaluate the accuracy of college students’ employment recommendations. The results show that the overall educational requirements of enterprises for the three significant positions of short video production, account operation and anchor are not high, and the percentage of those with education of high school or below or master’s degree or above is meager, neither exceeding 3.5%. The personalized employment recommendation algorithm can provide scientific and reasonable guidance for graduates’ employment, with an accuracy rate of up to 50% and a recommendation list length of N=30. When α=0.75, the personalized employment recommendation algorithm can obtain better recommendation performance with smaller recommendation list length. This paper provides new solutions for college students’ employment and valuable references and lessons for research in related fields.

Publisher

Walter de Gruyter GmbH

Reference13 articles.

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3. Domoto, E., & Okuhara, K. (2017). Employment impact analysis using variance analysis based on student data. International Journal of Japan Association for Management Systems, 9(1), 51-56.

4. Perozzi, B. (2019). Leadership development through transforming the student employment process. New Directions for Student Leadership, 2019(162).

5. Novikova, G. P., Ilkevich, K. B., Ovchinnikov, O. M., Zhdanov, S. P., Tsechoyev, V. K., & Shuaipov, M. M., et al. (2020). Social goals and social essence of human resources management: on student youth employment problem. Foundation for Environmental Protection and Research(2).

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