Paper
1 April 2024 Research on the construction of human resources job competency model based on text mining
Ding Liang
Author Affiliations +
Proceedings Volume 13081, Third International Conference on Advanced Manufacturing Technology and Electronic Information (AMTEI 2023); 1308119 (2024) https://doi.org/10.1117/12.3025875
Event: 2023 3rd International Conference on Advanced Manufacturing Technology and Electronic Information (AMTEI 2023), 2023, Tianjin, China
Abstract
Text mining is a hot research field that combines data mining with natural language processing. Using text mining technology, researchers can effectively integrate information to accurately retrieve and locate information, allowing users to find useful data efficiently. The job competency model is the cornerstone and pillar of human resources work. It contains a series of job competency elements. It costs a lot to build a competency model in the traditional way. In order to solve this problem, this article studies the use of text mining technology to build a competency model. For text clustering, this paper proposes a method based on an improved ant colony clustering model. This method makes full use of the self-organization of the ant colony clustering algorithm and its insensitivity to the order of previous data input, and improves the algorithm on its shortcomings. Experimental results show that the clustering precision rate, recall rate and 1F evaluation value of this algorithm can achieve the expected results.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Ding Liang "Research on the construction of human resources job competency model based on text mining", Proc. SPIE 13081, Third International Conference on Advanced Manufacturing Technology and Electronic Information (AMTEI 2023), 1308119 (1 April 2024); https://doi.org/10.1117/12.3025875
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KEYWORDS
Mining

Data modeling

Feature extraction

Education and training

Human resources

Machine learning

Classification systems

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