基于PC-树的关联规则挖掘方法

关联规则是数据挖掘的一种常用方法，特别是用在货篮分析中，而关联规则的经典算法Apriori及其改进算法的时间复杂度和空间复杂度都比较高，对于数据库更新、用户定义最小支持度等动态数据挖掘的成本太高。针对这种情况，提出了用PC-树寻找频繁项集的算法，实现高效的动态数据挖掘。

Mining methods of association rule based on PC-tree

Association rule is a classical method of data mining, especially at market analysis. But the temporal and spatial complicacy of apriori and apriori-like algorithmic are relatively high, and the cost is too expensive when they are used to deal with dynamic mining such as change of data, change of knowledge and change of user defined minimum support value and so on. The method to search frequent itemsets based on PC-tree (pattern count) is put forward, which is effective with dynamic data mining.