Machine learning in human resource system of intelligent manufacturing industry
Qing Xie
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.
Topics & Concepts
Matching (statistics)Key (lock)Resource (disambiguation)Human resourcesComputer scienceHuman resource management systemKnowledge managementManufacturingFactor (programming language)Artificial intelligenceManufacturing engineeringEngineeringHuman resource managementEngineering managementBusinessManagementComputer securityMarketingMathematicsStatisticsComputer networkProgramming languageEconomicsDigital Transformation in IndustryCollaboration in agile enterprisesAI and HR Technologies