基于BP神经网络的组织内部职位匹配度模型研究  

Research on Job Matching Degree Model in Organization Based on BP Neural Network

作　　者：肖蒙 XIAO Meng(Beijing Center for Cooperation in Patent Examination,Patent Office,State Intellectual Property Office,Beijing 100071,China)

机构地区：[1]国家知识产权局专利局专利审查协作北京中心,北京100071

出　　处：《移动信息》2024年第11期215-217,222,共4页Mobile Information

摘　　要：文中构建了一种基于BP神经网络的模型,用以实现企业人员与岗位之间的智能化匹配评估。通过收集员工和岗位特征数据,进行预处理和特征工程,建立3层BP网络结构,设计网络参数,使用人岗实际匹配样本进行监督式训练,得到匹配度模型。经过多轮训练优化,模型输出误差能控制在5%以内,达到了较高的评估精度。实验证明,该模型可以客观准确地评估人岗匹配度,为企业人力资源管理决策提供依据。This paper constructs a model based on BP neural networks to realize intelligent matching evaluation between employees and positions.By collecting employee and position characteristic data,preprocessing and feature engineering,a three-layer BP network structure is established,network parameters are designed,and the matching degree model is obtained by supervised training using actual matching samples of people and positions.After multiple rounds of training optimization,the output error of the model can be controlled within 5%,achieving a high evaluation accuracy.Experiments show that the model can objectively and accurately evaluate person-job fit,providing a basis for enterprise human resource planning decisions.

关 键 词：人力资源管理 人员岗位匹配 BP神经网络 模型训练 

分 类 号：TP399[自动化与计算机技术—计算机应用技术]