摘要
在分析现有的关联规则算法 IUA的基础上 ,指出了该算法的不足和错误之处 ,并加以改正 ,进而提出了一种改进的增量式更新算法 EIUA. EIUA算法解决了在数据库 D不变的情况下 ,当最小支持度和最小置信度二阈值发生变化时如何高效更新关联规则的问题 .
Mining association rules are a major aspect of data mining research, and maintaining discovered association rules are of equal importance. In this thesis, we analyze a previously proposed algorithm IUA and point out its disadvantages and errors and manage to correct these errors. Furthermore we have proposed an improved incremental maintaining algorithm EIUA. Assuming that database \$D\$ is not updated, EIUA has solved the problem of how to maintain discovered association rules efficiently when the two thresholds, minimum support and confidence, change. The experiments have shown the availability and superiority of the new algorithm.
出处
《系统工程理论与实践》
EI
CSCD
北大核心
2001年第11期14-19,共6页
Systems Engineering-Theory & Practice
