ABSTRACT

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.

中文翻译：

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智能制造行业人力资源系统中的机器学习

摘要

建立基于潜因子模型（LFM）和深度森林算法的混合模型，即多粒度级联森林（gcForest），优化整合智能制造行业人力资源系统中的关键招聘环节。LFM主要分析职位用户的浏览、应用、收集等方面的数据，gcForest主要分析用户和职位的匹配度。结果表明，基于LFM和gcForest的混合模型在智能制造行业人力资源系统员工的招聘中发挥了显着的作用。