针对形式背景,利用概念外延与内涵之间特殊的关系,结合粗糙集上下近似概念,提出一种粗糙概念格构造算法,属性约简后运用粗糙度进行挖掘,获取可靠性知识。在构造过程中,对节点属性进行判断,有效地降低算法的时间复杂度。实际案例分析结果表明,通过属性约简与粗糙度的结合,该算法可以有效地挖掘获取可靠性知识,为数据分析挖掘知识提供了一种可行的思路和方法。
For formal context,using the special relationship between the extension and intension of the concept,combined with down approximation concept in rough set,an algorithm for constructing rough concept lattice was proposed,in which roughness mining reliable knowledge was used after attribute reduction.In the construction process,the node properties were judged,which effectively reduced the time complexity of the algorithm.Practical case analysis demonstrates that by combining attribute reduction and roughness,the algorithm can effectively obtain reliable knowledge,which provides a workable thought and approach for data analysis mining knowledge.