Data association rules mining based on extension theory

摘要：

　　Discovering association rules is one of the most important tasks of data mining, that is, to find interesting associations or correlation relationship among a large set of data items.This paper describes the basic theory of Extenics, combines it with the present mining method of association rule to build the basic-element model of a relational database.On the basis of Apriori algorithm, through converting a multi-valued characteristic to Boolean value, using association rule mining algorithms and Extenics correlation ideologi cal, to carry out extension data association rule mining on a relation database and gain valu able association rules.And according to the implication and correlation of basic elements, to expand the association rules and generate the knowledge of extension transformation rules.

作者: T.C.Wang X.Y.Chen S.S.Zhong Z.D.Zhao

作者单位: College of Mechanical and Electrical Engineering Nanjing University of Aeronautics and Astronautics, College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics School of Mechantronics Engineering, Harbin Institute of Technology, Harbin, China Wuxi TJ Innova Auto-design Co., Ltd, Wuxi, Jiangsu Province, China

会议类型: 国际会议

会议名称: International Symposium on Extenics and Innovation Methods(可拓性与创新方法国际研讨会)

会议地点: 北京

会议语种:英文

页码: 115-120

在线出版日期: 2013-08-16（万方平台首次上网日期，不代表论文的发表时间）