Issue |
E3S Web Conf.
Volume 253, 2021
2021 International Conference on Environmental and Engineering Management (EEM 2021)
|
|
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Article Number | 02093 | |
Number of page(s) | 5 | |
Section | Big Data Environment Management Application and Industry Research | |
DOI | https://doi.org/10.1051/e3sconf/202125302093 | |
Published online | 06 May 2021 |
Analysis of Contemporary College Students’ Employment Model Based on Logit Model and Machine Learning
Xi’an Aeronautical Polytechnic Institute, Shanxi, Xian, 710089, China.
With the emergence of Internet big data, cloud computing, artificial intelligence and other new technologies, employment positions have also undergone profound changes. Small, medium and micro enterprises, new business forms and new models put forward new requirements for employment services in Colleges and universities. Starting from the current situation of College Students’ employment, this paper analyzes the reasons for the difficulty of College Students' employment and discusses how to solve the problem. In view of the group differences in the employment of college graduates, this paper puts forward some countermeasures and suggestions to speed up the development of service industry and promote employment, formulates the long-term strategy for the development of talent training institutions, and constructs an advanced account management system for college students. This paper analyzes the students' self-concept from the aspects of social needs, the change mode of school cultural concept and the lack of professional development. On the issue of College Students' employment, this paper analyzes the characteristics of College Students' employment and the needs of employers with the employment supply and demand as the main line. The results show that up to 26% of the graduates work in enterprises and at least 14% in administrative organs.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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