Selection algorithm of excellent talents in large enterprises based on entropy weighted clustering mining

Rui Lan; Jun Cheng; Liang Gao; Chao Liu

doi:10.1117/12.3033070

5 July 2024 Selection algorithm of excellent talents in large enterprises based on entropy weighted clustering mining

Rui Lan, Jun Cheng, Liang Gao, Chao Liu

Proceedings Volume 13184, Third International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024); 131843B (2024) https://doi.org/10.1117/12.3033070
Event: 3rd International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024), 2024, Kuala Lumpur, Malaysia

Abstract

Conventional talent selection algorithms for large enterprises mainly use induction and deduction to obtain selection competency characteristics, which is vulnerable to the influence of orientation consciousness, resulting in low matching degree of talent selection. Therefore, a new talent selection algorithm for large enterprises needs to be designed based on entropy weighted clustering mining. That is to say, based on entropy weighted clustering, a model for selecting talents in large enterprises is constructed, and an optimization algorithm for selecting talents in large enterprises is generated. The case analysis results show that the selection algorithm designed for the selection of outstanding talents in large enterprises has good selection effect, high selection matching degree, reliability and certain application value, and has made certain contributions to improving the comprehensive strength of Chinese enterprises and promoting the sustainable development of China.

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

Citation Download Citation

Rui Lan, Jun Cheng, Liang Gao, and Chao Liu "Selection algorithm of excellent talents in large enterprises based on entropy weighted clustering mining", Proc. SPIE 13184, Third International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024), 131843B (5 July 2024); https://doi.org/10.1117/12.3033070

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KEYWORDS

Mining

Mathematical optimization

Machine learning

Reliability

Education and training

Analytical research

Deep learning

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