基于信息标签体系的人员岗位匹配方法研究  

Study on staffer-post matching methods based on information tag hierarchy

作　　者：武国斌 张之明[1] 杨文欣 Wu Guobin;Zhang Zhiming;Yang Wenxin(College of Information Engineering,Engineering University of PAP,Xi′an 710086,China)

机构地区：[1]武警工程大学信息工程学院,陕西西安710086

出　　处：《网络安全与数据治理》2024年第9期41-48,共8页CYBER SECURITY AND DATA GOVERNANCE

摘　　要：人力资源管理信息化,既是信息化建设的重要内容,又是重要支撑和保证。随着人力资源数据不断积累,如何借助先进的科学技术从海量数据中挖掘出有价值的信息是当前研究领域的热点问题之一。本文依托于人力资源数据,提出了基于双向长短时记忆网络的图采样聚合模型生成模型标签,并构建了岗位和人员信息标签体系;提出了两种人岗匹配方法,实现了智能化的人员岗位匹配。实验表明,本文提出的模型方法取得了较好的效果,为相关数据信息的有效组织与管理提供了一种良好的解决方案,并为实现人力资源的智能化管理提供了有效借鉴。The information of human resource management is not only a significant content of information construction,but also an important support and guarantee.As human resource data keep accumulating,how to extract valuable information from massive data with the help of advanced science and technology is one of the hot issues in the current research field.Relying on human resource data,this paper proposed BGS model to generate model tags,constructed post and staffer information tag hierarchies,and proposed two methods to realize intelligent staffer-post matching.Experiments show that the proposed models and methods achieve better performance,providing a solution for the construction of the post and staffer information tag hierarchies,and providing an effective reference for the intelligent management of human resources.

关 键 词：人岗匹配 信息标签体系 图神经网络 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]