一种频繁加权概念格的批处理构造算法

A Batch Constructing Algorithm of Frequent Weighted Concept Lattice

概念格是知识表示和数据分析的一种有效工具,加权概念格是一种刻画内涵重要性的概念格结构.文中通过引入虚结点的概念,提出一种频繁加权概念格的批处理构造算法.该算法首先通过引入虚结点概念,证明频繁加权概念格是一个完全格,从而纠正先前张继福提出的频繁加权概念格结构中某些频繁加权概念结点不存在上下确界的缺陷.其次,采用自底向上的方法来生成频繁结点和虚结点,以及对应的边关系,从而降低频繁加权概念格构造的时空复杂性,提高批处理构造效率.最后在恒星光谱数据上的实验验证算法的正确性和有效性.

Concept lattice is an effective tool for knowledge representation and data analysis. Weighted concept lattice is a concept lattice structure which depicts the importance of intention. A batch constructing algorithm of frequent weighted concept lattice is proposed by using the concept of virtual node. Firstly, it is proved that frequent weighted concept lattice is a complete lattice by defining the concept of virtual node, thereby the defect of having no supremuIn/infimum for some frequent weighted nodes in previous frequent weighted concept lattics proposed by Zhang is avoided. Secondly, frequent node, virtual node and their edges are generated from the bottom to the top. Thus, the time and the storage complexity of constructing the lattice is reduced and the efficiency of batch constructing the frequent weighted concept lattice is improved. Finally, the experimental results validate the correctness and the validity of the by taking the star spectrum data as the formal contexts.