Abstract: Based on an actual dataset of college human resources，this paper analyzes the data mining technologies and processes applying on college human resources management，reduces and categorizes features by explorative data analysis，proposes the class label evaluating professors’ research abilities.Decision tree model analyzes some key factors concerning professors’ research abilities，cluster analysis objectively and effectively describes the professors’ present conditions and association rules show the relationship among teaching，research and social practices.The results of this study can be well explained.

Key words: data mining, human resources management, feature reduction, cluster analysis, association rule

摘要： 针对一个真实的高校人力资源数据集，分析了在高校人力资源管理中适用的数据挖掘技术与过程，通过探索性的数据分析进行了特征值的离散化和特征值的归约、特征选择和构造等方面的分析，并给出了衡量教学科研人员科研能力水平的分类标签建议。利用决策树模型分析了影响教师科研能力的几个关键因素，聚类分析对教师的现状进行了客观而有效地描述，关联规则技术描述了教学、科研和社会工作等几方面的关系。研究分析的结果具有较好的解释性。

关键词: 数据挖掘, 高校人力资源, 特征归约, 聚类分析, 关联规则