基于频繁模式树的负关联规则挖掘算法

典型的正关联规则仅考虑事务中所列举的项目。负关联规则不但要考虑事务中所包含的项目集，还必需考虑事务中所不包含的项目，它包含了非常有价值的信息。然而，对于负关联规则的研究却很少，仅有的几种算法也存在一定的局限性。为此，该文提出了一种基于FP-tree的负关联规则挖掘算法，该算法不但可以发现事务数据库中所有的负关联规则，而且整个过程只需扫描事务数据库两次，算法是有效和可行的。

Algorithm for Mining Negative Association Rules Based on Frequent Pattern Tree

Typical association rules consider only items enumerated in transactions.Such rules are referred to as positive association rules.Negative association rules also consider the same items,but in addition consider negated items(i.e.absent from transactions).Negative association rules are useful in market-basket analysis to identify products that conflict with each other or products that complement each other.Despite their usefulness,very few algorithms to mine them have been proposed to date.This paper presents an algorithm based on FP-tree to discover all negative association rules,which only scan database twice.The algorithm is efficient and practical.