期刊文献+

以概念格为背景的关联规则可视化 被引量:3

Visualization of Association Rules in Context of Concept Lattices
下载PDF
导出
摘要 传统的关联规则表示方法无法展示概念之间的本质关系,缺少对概念层面的认识,忽略了知识发现结果的共享等问题,而概念格作为一种能够生动简洁地体现概念之间泛化和例化关系的数据结构,在对关联规则可视化和发现潜在知识方面也有着独特的优势。提出了以概念格为背景的关联规则可视化方法,以概念为查找单元,在概念格中寻找需要展示的关联规则路径,将属性之间的关联关系扩展到概念层面,并给出了相对应的多模式规则的可视化的策略与算法。结合某校图书馆借书记录数据,进行关联规则分析与可视化实现。实验结果表明,该可视化方法在知识发现和共享方面具有良好的效果。 Traditional rule representation methods cannot show the nature of the relationship between concepts,the lack of understanding of the concept hierarchy,ignoring the problem such as sharing the results of knowledge discovery,and concept lattice as a data structure can succinctly vivid embodiment of generalization and instantiated in the relationship between the concepts,in terms of knowledge visualization and association rules found potential also has a unique advantage.This paper proposes an association rule visualization method with concept lattice as the background,takes concept lattice as the search unit,looks for the association rule path to be displayed in concept lattice,extends the association relation between attributes to the conceptual level,and gives the corresponding visualization strategy and algorithm of multipattern rules.Finally,the association rules are analyzed and visualized based on the library data.Experimental results show that the visualization method is effective in knowledge discovery and sharing.
作者 杨葛英 沈夏炯 史先进 张磊 YANG Geying;SHEN Xiajiong;SHI Xianjin;ZHANG Lei(School of Computer and Information Engineering,Henan University,Kaifeng,Henan 475004,China;Henan Key Laboratory of Big Data Analysis and Processing,Kaifeng,Henan 475004,China)
出处 《计算机工程与应用》 CSCD 北大核心 2021年第1期84-91,共8页 Computer Engineering and Applications
基金 国家自然科学基金(61402149) 河南省科技厅科技攻关计划基金(182102110065,182102210238) 河南省高等学校青骨干教师培养计划(2019GGJS040)。
关键词 概念格 关联规则 泛化和例化 知识发现 可视化 concept lattice association rules generalization and instantiated knowledge discovery visualization
  • 相关文献

参考文献11

二级参考文献106

  • 1KaisheQu,JiyeLiang,JunhongWang,ZhongzhiShi.The Algebraic Properties of Concept Lattice[J].Journal of Systems Science and Information,2004,2(2):271-277. 被引量:6
  • 2钱增瑾,辛燕,鞠时光.基于中药专利数据集的关联规则发现算法[J].计算机应用研究,2007,24(7):61-63. 被引量:2
  • 3Margaret H Dunham著,郭崇慧等译.数据挖掘教程[M].北京:清华大学出版社,2005,5.
  • 4胡可云,田凤占,黄宽厚.数据挖掘理论与应用[M].北京:清华大学出版社,北京交通大学出版社,2008.
  • 5GANTER B, WILLE R. Formal concept analysis : mathematical foundations [M]. Berlin: Springer-Verlag, 1999:17-35.
  • 6GUGISCH R. Many-valued context analysis using descriptions [ C]// Conceptual Structures: Broadening the Base, LNCS 2120. Berlin: Springer-Verlag, 2001 : 157 - 168.
  • 7NGUYEN T T, C HUI S C, CHANG K Y. A lattice-based approach for mathematical search using formal concept analysis [ J]. Expert Systems with Applications, 2012, 39(5):5820-5828.
  • 8BAL M, BAL Y, USTUNDAG A. Knowledge representation and discovery using formal concept analysis: an HRM application [ C]// WCE 2011: Proceedings of the World Congress on Engineering. London: Newswood, 2011 : 1068 - 1073.
  • 9CASSIO M, LEGRAND B. Extracting and visualising tree-like structures from concept lattices [ C]// IV'I 1: Proceedings of the 2011 15th International Conference on Information Visualisation. Washington, DC: IEEE Computer Society, 2011:261-266.
  • 10JULIEN B, FABRICE G, HENRI B. Interactive visual exploration of association rules with rule-focusing methodology [ J]. Knowledge and Information Systems, 2007, 13 (1) : 43 - 75.

共引文献107

同被引文献51

引证文献3

二级引证文献7

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部