Intelligent Matching Platform for University Students' Employability

DOI: https://doi.org/10.62517/jes.202602301

Author(s)

Linna Li1,*, Jiayu Li1, Yifan He1, Qingfeng Zhou2

Affiliation(s)

1School of Artificial Intelligence and Big Data, Henan University of Technology, Zhengzhou, Henan, China 2iFLYTEK Co., Ltd., Hefei, Anhui, China *Corresponding Author

Abstract

Therefore, this paper will introduce an intelligent matching platform for the employment prospects of college students and address the above issues. The Platform has been divided into a front-end and a back-end. Vue 3 and Element Plus are used for the user interface, Spring Boot and MyBatis for the back-end service, and JWT is used to ensure stateless authentication. Kafka is used for real-time data processing as a message queue, Flink performs stream-based intelligent matching calculations, and ClickHouse stores the matching results and statistics. The five dimensions of the multi-dimensional weighted scoring model are city, education level, major, salary and skills; accurate job recommendations are thus generated. An AI job-seeking assistant based on the DeepSeek-V3 large language model will offer real-time career advice. The three types of users for the system are students, enterprises and administrators, and all have data dashboards for employment monitoring. Experimental tests of less than 100 concurrent users showed that the average response time was less than 500 milliseconds, and thus the platform had effectively improved the accuracy of work matching, simplified employment management, and raised the general standard of university employment services.

Keywords

Intelligent Job Matching; Employment Service Platform; Real‑Time Data Processing; Hybrid Recommendation Algorithm; Multi‑Dimensional Weigscoring Model; Vue 3

References

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