Mining Fuzzy Association Rules in Quantitative Databases

摘要：

　　In this paper,we introduce a novel technique for mining fuzzy association rules in quantitative databases.Unlike other data mining techniques who can only discover association rules in discrete values,the algorithm reveals the relationships among different quantitative values by traversing through the partition grids and produces the corresponding Fuzzy Association Rules.Fuzzy Association Rules employs linguistic terms to represent the revealed regularities and exceptions in quantitative databases.After the fuzzy rule base is built,we utilize the definition of Support Degree in data mining to reduce the rule number and save the useful rules.Throughout this paper,we will use a set of real data from a wine database to demonstrate the ideas and test the models.

关键词： Fuzzy set association rule data mining support degree

作者: Yiming Bai Xianyao Meng Xinjie Han

作者单位: Room 303,Information Science and Technology Building B,Dalian Maritime University,China

会议类型: 国际会议

会议名称: 2012 International Applied Mechanics,Mechatronics Automation Symposium(2012应用力学,机电一体化自动化国际研讨会)(IAMMAS2012)

会议地点: 沈阳

会议语种:英文

页码: 2003-2007

在线出版日期: 2012-09-07（万方平台首次上网日期，不代表论文的发表时间）