面向人口收入管理的数据挖掘研究与应用  

Research and application of data mining based on census income management

作　　者：赵京胜[1] 张鹏[1] 孙宇航[1] 

机构地区：[1]青岛理工大学通信与电子工程学院,山东青岛266033

出　　处：《计算机工程与设计》2014年第3期885-889,899,共6页Computer Engineering and Design

摘　　要：针对经典Apriori算法和K-Means算法分别进行了改进,提出一种优化候选集产生的MA-Apriori(matrix-Apriori)算法和一种确定初始聚类中心点选取的IM-K-Means(improve-K-Means)算法,将这两种改进算法与人口收入管理系统相结合。通过理论和性能分析及实例应用验证了改进算法的效率,搭建基于人口收入信息管理的数据挖掘系统。该系统使MA-Apriori算法和IM-K-Means算法平台化,完善了人口收入数据方面的管理,为收入分类和评价提供了科学的新方法。The respective improvement to the classical Apriori algorithm and K-Means algorithm are carried on, accordingly a MA-Apriori algorithm that optimizes the process of producing candidate and an IM-K-Means algorithm that determines initial clustering centriods are put forward, and combining them with census income management system. First of all, the efficiency of the improved algorithm is proved with the support of relevant theories, performance analysis and examples. Then a system plat- form of data mining is built based on the census income information management. The system makes the MA-Apriori algorithm and IM-K-Means algorithm platformed, improves the management of census income data, and provides a scientific classification and evaluation for income.

关 键 词：APRIORI算法 K-MEANS算法 人口收入 数据挖掘 管理系统 

分 类 号：TP399[自动化与计算机技术—计算机应用技术]