Elimination Algorithm of Redundant Association Rules Based on Domain Knowledge

摘要：

Many association rule mining algorithms have been developed to extract interesting patterns from large databases. However, a large amount of knowledge explicitly represented in domain knowledge has not been used to reduce the number of association rules. A significant number of known associations are unnecessarily extracted by association rule mining algorithms. The result is the generation of hundreds or thousands of non-interesting association rules. This paper presents an algorithm named DKARM, which takes into account not only database itself, but also related domain knowledge, so as to eliminate extraction of known associations in domain knowledge. Experiments show this algorithm can reasonably eliminate redundant rules, and effectively reduce the number of rules.

关键词： Data Mining Association Rules Domain Knowledge Redundant Rules

作者: Jing Zhang Bin Zhang Zihua Wang Lijun Shi

作者单位: School of Computer and Information Hefei University of Technology Hefei, Anhui, China USTC E-Business Technology Co., Ltd Hefei, Anhui, China

会议类型: 国际会议

会议名称: 2010 Seventh Web Information System and Applications Conference(第七届全国web信息系统及其应用学术会议)

会议地点: 呼和浩特

会议语种:英文

页码: 13-16

在线出版日期: 2010-08-20（万方平台首次上网日期，不代表论文的发表时间）