基于数据挖掘的公共管理部门绩效评价研究

Research on public administration sector performance evaluation based on data mining

以提升海量数据情况下公共管理部门绩效评价有效性为目标,研究基于数据挖掘技术的公共管理部门绩效评价。利用数据挖掘技术的关联规则数据挖掘方法挖掘公共管理部门绩效相关数据,关联规则数据挖掘方法利用支持度、置信度和关联度三个指标挖掘数据间关联规则,建立公共管理部门绩效评价体系,依据所建立的公共管理部门绩效评价体系利用模糊综合评价方法通过建立判断矩阵、计算权值、构建模糊综合评价模型三部分实现公共管理部门绩效评价。实验结果表明,所研究方法可有效评价公共管理部门绩效,数据量高达10 GB时评价时间仍低于10 s,实用性高。

With the goal of improving the effectiveness of the performance evaluation of public administration sectors under the condition of massive data,the public administration sector performance evaluation based on data mining technology is studied.The association rule mining method of the data mining technology is used to mine the performance⁃related data of the public administration sector.The association rule mining method is adopted to mine the association rules among the data by the three indicators of support degree,confidence degree and association degree,so as to establish a performance evaluation system for the public administration sector.According to the established performance evaluation system,the fuzzy comprehensive evaluation method is used to implement the performance evaluation of public administration sectors with three steps of establishing a judgment matrix,calculating weights and constructing a fuzzy comprehensive evaluation model.The experimental results show that the method studied can effectively evaluate the performance of public administration sectors,its evaluation time is still less than 10 s when the data volume is as large as 10 Gb,and it is highly practical.