【摘要】 负关联规则A→ B(或者 A→B, A→ B)描述的是项目之间的互斥关系,其与传统的关联规则有着同样重要的作用.然而,负关联规则和传统正关联规则的挖掘有很大不同,因为负关联规则隐藏在数量巨大的非频繁项集中.因此提出一种新的挖掘horn子句类型负关联规则的算法,并且实验证明是行之有效的.更多还原

【Abstract】 Negative association rules (NAR) catch mutually-exclusive correlations among items.They play important roles just as traditional association rules (TAR) do.For example,in stock market surveillance based on alert-logs,NARs detect which alerts are false.There are essential differences between mining TARs and NARs because NARs are hidden in infrequent itemsets.This paper presents a new algorithm for mining horn-clause-based negative association rules.To evaluate this algorithm,the authors have illustrated the efficiency by a group of experiments.更多还原