The Employment Management for College Students Based on Deep Learning and Big Data

Abstract

College graduates face increasing employment pressure due to the continuous expansion of colleges and universities' enrollment scales. It highlights the shortcomings of college students' employability, and these deficiencies can be improved and enhanced through the role of ideological and political education. Firstly, this paper summarizes the current situation of college students' employment management at this stage and finds countermeasures to improve their employability to help them correctly understand their employment situation. Secondly, the reasons for the lack of ideological and political education in cultivating college students' employability are emphasized to clarify the relationship between ideological and political education and college students' employment management. Besides, specific suggestions are put forward on the issue of cultivating college students' employability. Finally, the deep learning (DL) recommendation model is used to effectively connect the correlation between student data and enterprise information to improve the employment rate and employment satisfaction of colleges and universities, and the two are jointly trained. The experimental results show that: 1) The proposed model can mine the characteristics of students and enterprises and conduct feature interaction with a good hit rate; 2) The proposed model can interact with the two tasks and mine the relationship information to improve the performance of the recommended task. This paper aims to use DL methods to analyze and construct the portrait of college students' employability needs and study the accurate recommendation system based on the employment matching degree of college students to improve employment management and ideological and political education methods.