Research on the evaluation model of human job matching based on improved entropy method

Rui Lan; Liang Gao; Chao Liu

doi:10.1117/12.3049482

8 November 2024 Research on the evaluation model of human job matching based on improved entropy method

Rui Lan, Liang Gao, Chao Liu

Author Affiliations +

Proceedings Volume 13416, Fourth International Conference on Advanced Algorithms and Neural Networks (AANN 2024); 134161Y (2024) https://doi.org/10.1117/12.3049482
Event: 2024 4th International Conference on Advanced Algorithms and Neural Networks, 2024, Qingdao, China

Abstract

In view of the needs of human resource information management, this paper carries out data analysis based on the relevant data of XX enterprise human resource platform, and builds a human-post matching model combined with big data algorithm model technology. First of all, the unstructured data is standardized, and then the multi-attribute cross-feature calculation of personnel is realized to reduce dimension, and the historical data is analyzed to construct combined features, and the potential connection of features is explored by combining big data analysis technology. The evaluation index system of person-post matching was constructed, and the indexes at each level were modified, and relevant analysis such as correlation analysis and principal component analysis was carried out to finally determine the evaluation index of this study. To achieve a more scientific and efficient evaluation and control of talents, to ensure that the human resources evaluation work is targeted and efficient.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Rui Lan, Liang Gao, and Chao Liu "Research on the evaluation model of human job matching based on improved entropy method", Proc. SPIE 13416, Fourth International Conference on Advanced Algorithms and Neural Networks (AANN 2024), 134161Y (8 November 2024); https://doi.org/10.1117/12.3049482

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