基于区间概念格的规则优化方法与应用

区间概念格理论是在区间参数基础上提出的一种新的对象挖掘方法，它能够更精确地处理不确定信息。区间参数α,β]]决定了区间概念和格结构，并对区间关联规则产生影响。针对区间参数对关联规则的控制和优化问题，首先提出了基于参数变化的区间概念格结构更新算法，随着区间参数等步长变化，对初始格结构进行更新；然后在此基础上进一步挖掘各区间参数下的关联规则，发现区间参数和关联规则之间的复杂联系，给出了规则库优化算法，该算法通过调整参数达到控制和优化规则的目的；最后对决策形式背景进行规则提取并验证了区间参数对关联规则的具体影响。

Rule optimization method and application based on interval concept lattice

Interval concept lattice theory is a new method of mining objects based on interval parameters. It can accurately deal with uncertain information. The interval parametersα,β]]determine interval concepts and structure of lattice, then affect interval association rules. For the control and optimization of association rules, it firstly puts forward updating algorithm of concept lattice structure based on the change of parameters. With the change of interval parameters by equal step, it updates the original lattice structure. Secondly it mines association rules on the basis of interval concept lattice, and finds the complicated relationship between interval parameters and association rules to control and optimize rules, at the same time rule base optimization algorithm is proposed. Finally it uses the example with decision formal context to verify the relationship between association rules and interval parameters.