加权概念格的渐进式构造及其关联规则提取

概念格的每个结点本质上是一个最大项目集,非常有利于关联规则的提取。然而目前对于概念格的研究,一般都假定由属性集所组成概念格的内涵同等重要,而在现实数据库中,组成内涵的属性重要性往往是不同的,因此,内涵并非同等重要。为了充分利用概念格实现关联规则提取,提出了一种新的概念格结构:加权概念格,并给出其渐进式构造算法及基于该格结构上的关联规则提取算法,同时给出算法分析以说明其可行性。

The Construction of Weighted Concept Lattice and Association Rule Extraction

The intension of each node of the concept lattice is virtually one largest item set,and it is benefit for the association rules extraction.However,the present research presumes that all the intensions of the concept lattice are equally important.In practice,the importance of the attributes consisting of the intension is often different,so the importance of the intension is not the same.In order to make the best use of the concept lattice for the association rules extraction,this paper puts forward one new concept lattice:weighted concept lattice.Moreover,it offers one association rule extraction algorithm and algorithm analysis that illustrates its practicability.