计算机科学 ›› 2010, Vol. 37 ›› Issue (9): 180-183.

• 数据库与数据挖掘 • 上一篇    下一篇

一种基于概念矩阵的概念格生成算法

陈震,张娜,王甦菁   

  1. (吉林大学计算机科学与技术学院 长春130012)
  • 出版日期:2018-12-01 发布日期:2018-12-01
  • 基金资助:
    本文受国家高技术研究发展计划(863计划)(No. 2007AA11z124) , 国家科技支撑计划子课题(No. 2006BAJ18B02-06)资助。

New Algorithm of Generating Concept Lattice Based on Concept-matrix

CHEN Zhen,ZHANG Na,WANG Su-jing   

  • Online:2018-12-01 Published:2018-12-01

摘要: 概念格作为形式概念分析理论中的核心数据结构,在机器学习和数据挖掘等领域有着广泛的应用。构造概念格十分重要,针对此引入了概念矩阵思想,提出了基于概念矩阵的概念格生成算法CMCG(Concept Matrix Based Concepts Generation)。该算法从格的顶端节点开始构造,基于概念矩阵,利用属性的秩为每个节点生成它的所有子节点,完成子节点到父节点之间的链接,并生成哈斯图。给出了这种算法的理论依据。最后提供了这一算法的伪码,并通过实验证明了CMCG算法的时间性能优于Lattice算法。

关键词: 概念格,概念矩阵,矩阵的秩,形式概念分析,哈斯图

Abstract: Concept lattice,the core data structure in FCA(Formal Concept Analysis),has been widely used in machine learning and data mining. In its applications, building concept lattice is very important, for which an efficient algorithm CMCG based on concept matrix was put forward. The algorithm started from the top node of the lattice, generated all subnodes for each node using the rank of the concept matrix's attributes,completed the link between the subnodes and their parent, and generated the Hasse graph. The validity of the algorithm was proved in theory. In the end, the pseudo code of CMCG algorithm was given and that performance of CMCG is superior in time to lattice algorithm was proved by experiments.

Key words: Concept lattice, Concept matrix, Rank of matrix, Formal concept analysis, Hasse graph

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!