基于决策树算法的人力资源推荐研究

Research on Human Resource Recommendation Based on Decision Tree Algorithm

当前人力资源推荐方法存在过程复杂,推荐错误大,难以满足人力资源管理的实际应用要求,为了解决当前人力资源推荐过程中存在的问题,以提高人力资源推荐精度为目标,提出了基于决策树算法的人力资源推荐方法。首先分析人力资源推荐的原理,并采集大量与人力资源推荐相关的数据,然后采用聚类分析算法对人力资源推荐数据进行预处理,最后采用决策树算法建立人力资源推荐模型,根据模型进行人力资源推荐,并采用具体实例进行了人力资源推荐验证性分析。结果表明,提出的方法人力资源推荐精度超过90%,能够获得十分理想的人力资源推荐结果,人力资源推荐效果要明显优于当前其它人力资源推荐方法。

At present,the process of human resource recommendation is complex,and the recommendation error is large,it is difficult to meet the practical application requirements of human resource management.In order to solve the problems existing in the process of human resource recommendation and improve the accuracy of human resource recommendation,a method based on decision tree algorithm is proposed.Firstly,the principle of human resource recommendation is analyzed,and a large number of related data are collected.Then,the clustering analysis algorithm is used to preprocess the data.Finally,the decision tree algorithm is used to establish the human resource recommendation model.According to the model,human Resource Recommendation is carried out.Finally,the verification analysis of human resource recommendation is carried out with specific examples.The results show that the human resource recommendation accuracy of this method is more than 90%,and the effect is obviously better than other current human resource recommendation methods.