基于人工智能的人力资源数据整合系统

Human resource data integration system based on Artificial Intelligence

针对人力资源原始数据集成度低等问题,提出一种基于隐语义模型的人力资源数据整合系统。为实现对人力资源数据的整合与挖掘,首先对人力资源数据进行预处理,并构建OLAP数据仓库;然后提出一种结合隐语义模型和深度森林模型的人力资源推荐算法,通过求职者的行为,挖掘求职者可能的潜在岗位,进而实现匹配。测试结果表明,本研究提出的人工智能推荐,无论是在召回率,还是在F1值上,均要优于单一的隐语义模型和深度森林算法。

Aiming at the problem of low integration degree of human resource original data,this paper proposes a human resource data integration system based on implicit semantic model.In order to realize the integration and mining of human resource data,we first preprocess the human resource data and build an OLAP data warehouse.Then a human resource recommendation algorithm is proposed based on hidden semantic model and deep forest model.Through the behavior of job seekers,the potential positions of job seekers is mined,and then the matching is realized.The test results show that the AI recommendation proposed in this study whether in recall rate or F1 value,and it is due to a single implicit semantic model and deep forest algorithm.