中文摘要：

对概念格在关联规则挖掘中的应用进行了研究。通过将概念格的外延和内涵分别与事务数据库中的事务和特征相对应，可以从概念格上产生频繁项集，进而挖掘关联规则。提出了一种基于概念格的关联规则挖掘方法，在背景中对象约简的基础上，构造出对象约简后的概念格，从新的概念格中先产生基本规则集，再根据用户给出的支持度阈值从基本规则集中挖掘出对用户有意义的规则，并给出了算法描述。该方法求出的关联规则和利用Apriori算法求出的结果是一致的。

英文摘要：

The application of concept lattice in association rules mining is studied. The frequent items sets can be generated from concept lattice by corresponding extensions and intensions of the concept lattice to transactions and characteristics in the transaction database, and then mining association rules. A method for mining association rules based on concept lattice is presented, building the concept lattice on the basis of objects reductions of the context, the basic rules set can be generated from the new concept, and then mining the meaning rules for users according to the threshold is given by users from the basic rules set, and an algorithm is given to describe the method. Association rules computed by the method are coherent with results computed by the Apriori algorithm.