概念格是形式概念分析申的核心数据结构,随着数据量的日益剧增,概念格的构造效率始终是关键.本文首先引入横向分块概念格,给出其若干结论;针对横向分块概念格构造过程中存在冗余信息,提出一种基于剪枝的横向分块概念格渐进式构造算法PHCL,从而进一步提高了概念格的构造效率;最后采用恒星天体光谱数据作为形式背景,实验验证了算法PHCL的正确性和有效性.
Concept lattice is the core data structure of formal concept analysis. However, with the sharp increasing of the data to deal with and analyze, the efficiency of its construction became the key problem. In order to improve the construction efficiency of concept lattice, this paper firstly introduced horizontal partitioning concept lattices, and giving some conclusions. Secondly, an incremental algorithm PHCL of constructing horizontal partitioning concept lattices based on pruning is presented through eliminating the redundancy information in the construction process by pruning. The experimental results prove the correctness and validity of the algorithm PHCL by taking the celestial spectrum data as the formal context.