Influence of data mining technology in information analysis of human resource management on macroscopic economic management.

The purposes are to manage human resource data better and explore the association between Human Resource Management (HRM), data mining, and economic management. An Ensemble Classifier-Decision Tree (EC-DT) algorithm is proposed based on the single decision tree algorithm to analyze HRM data. The inv...

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Autor principal:	Ai Zhang
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/b37377df752c4d1685d8e84c24fa42bc
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spelling	oai:doaj.org-article:b37377df752c4d1685d8e84c24fa42bc2021-11-25T06:19:10ZInfluence of data mining technology in information analysis of human resource management on macroscopic economic management.1932-620310.1371/journal.pone.0251483https://doaj.org/article/b37377df752c4d1685d8e84c24fa42bc2021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0251483https://doaj.org/toc/1932-6203The purposes are to manage human resource data better and explore the association between Human Resource Management (HRM), data mining, and economic management. An Ensemble Classifier-Decision Tree (EC-DT) algorithm is proposed based on the single decision tree algorithm to analyze HRM data. The involved single decision tree algorithms include C4.5, Random Tree, J48, and SimpleCart. Then, an HRM system is established based on the designed algorithm, and the evaluation management and talent recommendation modules are tested. Finally, the designed algorithm is compared and tested. Experimental results suggest that C4.5 provides the highest classification accuracy among the single decision tree algorithms, reaching 76.69%; in contrast, the designed EC-DT algorithm can provide a classification accuracy of 79.97%. The proposed EC-DT algorithm is compared with the Content-based Recommendation Method (CRM) and the Collaborative Filtering Recommendation Method (CFRM), revealing that its Data Mining Recommendation Method (DMRM) can provide the highest accuracy and recall, reaching 35.2% and 41.6%, respectively. Therefore, the data mining-based HRM system can promote and guide enterprises to develop according to quantitative evaluation results. The above results can provide a reference for studying HRM systems based on data mining technology.Ai ZhangPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 5, p e0251483 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Ai Zhang Influence of data mining technology in information analysis of human resource management on macroscopic economic management.
description	The purposes are to manage human resource data better and explore the association between Human Resource Management (HRM), data mining, and economic management. An Ensemble Classifier-Decision Tree (EC-DT) algorithm is proposed based on the single decision tree algorithm to analyze HRM data. The involved single decision tree algorithms include C4.5, Random Tree, J48, and SimpleCart. Then, an HRM system is established based on the designed algorithm, and the evaluation management and talent recommendation modules are tested. Finally, the designed algorithm is compared and tested. Experimental results suggest that C4.5 provides the highest classification accuracy among the single decision tree algorithms, reaching 76.69%; in contrast, the designed EC-DT algorithm can provide a classification accuracy of 79.97%. The proposed EC-DT algorithm is compared with the Content-based Recommendation Method (CRM) and the Collaborative Filtering Recommendation Method (CFRM), revealing that its Data Mining Recommendation Method (DMRM) can provide the highest accuracy and recall, reaching 35.2% and 41.6%, respectively. Therefore, the data mining-based HRM system can promote and guide enterprises to develop according to quantitative evaluation results. The above results can provide a reference for studying HRM systems based on data mining technology.
format	article
author	Ai Zhang
author_facet	Ai Zhang
author_sort	Ai Zhang
title	Influence of data mining technology in information analysis of human resource management on macroscopic economic management.
title_short	Influence of data mining technology in information analysis of human resource management on macroscopic economic management.
title_full	Influence of data mining technology in information analysis of human resource management on macroscopic economic management.
title_fullStr	Influence of data mining technology in information analysis of human resource management on macroscopic economic management.
title_full_unstemmed	Influence of data mining technology in information analysis of human resource management on macroscopic economic management.
title_sort	influence of data mining technology in information analysis of human resource management on macroscopic economic management.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/b37377df752c4d1685d8e84c24fa42bc
work_keys_str_mv	AT aizhang influenceofdataminingtechnologyininformationanalysisofhumanresourcemanagementonmacroscopiceconomicmanagement
_version_	1718413946154647552

Influence of data mining technology in information analysis of human resource management on macroscopic economic management.

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