Machine learning in human resource system of intelligent manufacturing industry

被引：9
|
作者：
Xie, Qing [1 ,2 ]
机构：
[1] Univ Putra Malaysia, Fac Econ & Management, Dept Management & Mkt, Serdang 43400, Selangor, Malaysia
[2] Anshun Univ, Sch Econ & Management, Anshun, Peoples R China
来源：
ENTERPRISE INFORMATION SYSTEMS | 2022年 / 16卷 / 02期
基金：
美国国家科学基金会;
关键词：
Machine learning; human resources; model; algorithm; ARTIFICIAL-INTELLIGENCE; FUTURE; CHALLENGES;
D O I：
10.1080/17517575.2019.1710862
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A hybrid model based on latent factor model (LFM) and deep forest algorithm, namely multi-Grained Cascade forest (gcForest) was established to optimise and integrate the key recruitment links in the human resource system of intelligent manufacturing industry. The LFM mainly analysed the browsing, application, collection and other aspects of data of job users, and the gcForest mainly analysed the matching degree of users and positions. The results showed that the hybrid model based on LFM and gcForest played a significant role in the recruitment of human resource system employees in the intelligent manufacturing industry.
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页码：264 / 284
页数：21
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