基于灰色关联分析的高感兴趣度数据挖掘算法研究  

Research on algorithm to data mining with high interestingness based on gray relational analysis

作　　者：刘宏[1] 吴江[2] 耿国华[2] 钟生海[1] 

机构地区：[1]安康学院计算机科学系,陕西安康725000 [2]西北大学信息科学与技术学院,陕西西安710127

出　　处：《计算机工程与设计》2008年第16期4242-4244,4248,共4页Computer Engineering and Design

基　　金：国家自然科学基金项目(60573179);安康学院基金项目(AYQDZR200632)

摘　　要：数据挖掘与知识评价相结合是数据挖掘工作研究的重要方面,也是发挥数据挖掘潜力的重要手段。讨论了数据挖掘和知识评价的结合方式以及灰色关联分析,提出并实现了用灰色关联分析方法构建"感兴趣产生器"并结合关联规则的数据挖掘框架及算法。最后,通过实例证明了该算法挖掘效率高、挖掘效果好,挖掘结果有较高的用户感兴趣度。It is important that data mining is combined with knowledge evaluation, and it is as well efficient means to realize potential of data mining. Problems about combining data mining with knowledge evaluation, and gray relational analysis are discussed. An architecture and algorithm to data mining combined gray relational analysis as creator of interestingness with association rules is put forward and implemented. Finally, it is proved by an example that the algorithm is of high efficiency, good purpose and that the result of data mining is of higher using interestingness.

关 键 词：灰色关联分析 知识评价 感兴趣产生器 关联规则 数据挖掘 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]