Proceedings of the 3rd International Conference on Internet Technology and Educational Informatization, ITEI 2023, November 24–26, 2023, Zhengzhou, China

Research Article

Analysis of Employment Pressure of Local University Graduates Based on Time Relaxation Take Computer Major as an Example

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  • @INPROCEEDINGS{10.4108/eai.24-11-2023.2343707,
        author={Zhihong  Zhong and Honglang  Wei},
        title={Analysis of Employment Pressure of Local University Graduates Based on Time Relaxation Take Computer Major as an Example},
        proceedings={Proceedings of the 3rd International Conference on Internet Technology and Educational Informatization, ITEI 2023, November 24--26, 2023, Zhengzhou, China},
        publisher={EAI},
        proceedings_a={ITEI},
        year={2024},
        month={4},
        keywords={relaxation of employment time; decision tree; data mining; chinese colleges and universities},
        doi={10.4108/eai.24-11-2023.2343707}
    }
    
  • Zhihong Zhong
    Honglang Wei
    Year: 2024
    Analysis of Employment Pressure of Local University Graduates Based on Time Relaxation Take Computer Major as an Example
    ITEI
    EAI
    DOI: 10.4108/eai.24-11-2023.2343707
Zhihong Zhong1,*, Honglang Wei1
  • 1: Qiannan Normal University for Nationalities
*Contact email: zzhstudio@126.com

Abstract

Based on the employment datas of local college graduates in China, the time relaxation is defined by the initial employment time of graduates. With time relaxation as an indicator,the degree of employment pressure for graduates is divided into four levels: urgent, normal, loose, and comfortable,then,the employment pressure for graduates is classified. Based on various characteristics of graduates such as gender, ethnicity, poverty, major, political countenance, Normal student category, and nature of employment units, conduct a multidimensional analysis of employment pressure; Finally, the C4.5 decision tree data mining algorithm is used for principal component analysis to obtain the key features that affect the time relaxation, the results indicate that the key characteristics are political countenance, Normal student category, poverty category, and ethnicity. Through datas analysis, obtain numerous meaningful information that can guide graduates' employment decisions.