广义关联规则基及其挖掘算法

为了解决传统的关联规则挖掘中产生大量规则的问题，提出了项目集上闭集和广义关联规则基的概念，并得出了闭项目集的上闭集是它本身、上闭集是惟一的等性质．基于这些性质，给出了事物数据库的广义关联规则基，不仅保留了数据库中所有关联规则的信息，而且规则有一致的结构，从而最大限度地减少了规则生成的数量．此外，还设计了广义关联规则基的挖掘算法，并通过实例验证了它的正确性．

Generalized Association Rule Base and Its Mining Algorithm

To solve the problem that the existing algorithms of mining association rules result in a number of rules, upper closed set of an item set and generalized association rule base were defined. And some important propositions were obtained, e.g. the upper closed set of an item set exists uniquely and is the item set. From these propositions, the generalized association rule base of a transaction database was proposed. It contains the information of all the association rules in the database and the rules have a uniform structure. As a result, the number of rules can be reduced as many as possible. In addition, a mining algorithm for generalized association rule bases was proposed and its validation was proven using an example.