期刊文献+

强协调决策形式背景的概念格属性约简 被引量:2

Attribute reduction theory of concept lattice based on strongly decision formal contexts
在线阅读 下载PDF
导出
摘要 运用概念的闭标记研究了强协调决策形式背景的核心属性问题.通过概念的闭标记得到了判定强协调决策形式背景的协调集的方法,并且定义了计算约简集的函数,从而得到了约简集,最后通过简单的集合运算得出协调决策形式背景的核心属性. The core attribute of a strongly decision formal context by the closed label of a concept was studied .Using the closed label of a concept ,a method of judging a set whether if is a consistent set of the strongly decision formal context was given .Further ,a function of computing the reductions was defined , and the reduction set was obtained .Finally ,through a collection of simple set operations ,the core attrib-ute of the strongly decision formal context was achieved .
作者 王艳盼 李涛
机构地区 西北大学数学系
出处 《纺织高校基础科学学报》 CAS 2013年第3期351-354,共4页 Basic Sciences Journal of Textile Universities
基金 国家自然科学基金资助项目(11071281 607032117)
关键词 决策形式背景 概念格 闭标记 属性约简 decision formal context concept lattice closed label attribute reduction
  • 相关文献

参考文献13

  • 1WILLE R. Restructuring lattice theory: an approach based on hierarchies of eoncepts[M]. Ordered Sets, Dordrecht- Boston.. Reidel, 1982 .. 445-470.
  • 2GANTER B,WILLE R. Formal concept analysis., mathematical foundations[M]. New York:Sprin4ger-Verlag, 1999..284.
  • 3HOT B. Incremental conceptual clustering in the framework of Galois lattice[M-]//Techniques and Applications. Sin- gapore: World Scientific, 1997 .. 49-64.
  • 4KENT R E,BOWMAN C M. Digital libraries, conceptual knowledge systems and the nebula interface [R]. Arkansas.. University of Arkansas, 1995.
  • 5CORBETT D,BURROW A L. Knowledge reuse in SEED exploiting conceptual graphs[C]//Proceeding of the 4th In- ternational Conference on Conceptual Graphs (ICCSI96). Heidelberg:Springer, 1996 : 56-60.
  • 6SUTTON A,MALETIC J I. Recovering UML class models from C-k-+: a detailed explanation[J]. Inf Softw Tech, 2007,49(3) .. 212-229.
  • 7SIFF M,REPS T. Identifying modules via concept analysis[C]//Internatinnal Conference on Software Maintenance. Washington,DC: IEEE Computer Society, 1997 : 170-179.
  • 8张文修,魏玲,祁建军.概念格的属性约简理论与方法[J].中国科学(E辑),2005,35(6):628-639. 被引量:203
  • 9魏玲,祁建军,张文修.决策形式背景的概念格属性约简[J].中国科学(E辑),2008,38(2):195-208. 被引量:74
  • 10LI J H,MEI C L,LV Y J. A heuristic knowledge-reduction method for decision formal contexts[J]. Computers and Mathematics with Applications,2011,61(4) : 1 096-1 106.

二级参考文献27

  • 1张文修,魏玲,祁建军.概念格的属性约简理论与方法[J].中国科学(E辑),2005,35(6):628-639. 被引量:203
  • 2ZHANG Wenxiu,WEI Ling,QI Jianjun.Attribute reduction theory and approach to concept lattice[J].Science in China(Series F),2005,48(6):713-726. 被引量:76
  • 3Wille R. Restructuring lattice theory: An approach based on hierarchies of concepts[C]. In: Rival I, ed. Ordered Sets Dordrecht-Boston : Reidel, 1982. 445-470.
  • 4Oosthulzen G D. The Application of Concept Lattice to Machine Learning[R]. Technical Report,University of Pretoria, South Africa, 1996.
  • 5Ho T B. Incremental conceptual clustering in the framework of Galois lattice[C]. In: Lu H, Motoda H, Liu H, eds. KDD:Techniques and Applications. Singapore World Scientific,1997.49-64.
  • 6Siff M, Reps T. Identifying modules via concept analysis[C]. In: Harrold M J, Visaggio G, eds. International confercence on software maintenance. Bari, Italy Washington, DC : IEEE Computer Society, 1997.170-179.
  • 7Sehmitt I, Saake G. Merging Inheritances for scheme integration based on concept lattices[EB/OL], http://www. Mathematic. tu-dram stadt, de/ags/agl.
  • 8Oosthuizen G D. The Application of Concept Lattice to Machine Learning. Technical Report, University of Pretoria, South Africa, 1996.
  • 9Ho T B. Incremental conceptual clustering in the framework of Galois lattice. In: Lu H, Motoda H, Liu H, eds. KDD: Techniques and Applications. Singapore: World Scientific, 1997. 49~64.
  • 10Kent R E. Bowman C M. Digital Libraries, Conceptual Knowledge Systems and the Nebula Interface. Technical Report, University of Arkansas, 1995.

共引文献246

同被引文献20

  • 1马垣,曾子维,迟呈英,等.形式概念及其新进展[M].北京:科学出版社.2010:170—181.
  • 2Wile R.Restructuring lattice theory:an approach based on hierarchies of concepts[M].Dordrecht Boston:Reidel,1982:445-470.
  • 3Liu Xulong,Hong Wenxue.Using formal concept analysis to visualize relationships of syndromes intraditional Chinese medicine[J].Medical Biometrics,LNCS,2010,6165:315-324.
  • 4Cheng Chingwu,Yao Hongqing,Wu Tsungchih.Applying data mining techniques to analyze the causes of major occupational accidents in the petrochemical industry[J].Journal of Loss Prevention in the Process Industries,2013,26(6):1269-1278.
  • 5Chen Chunhsien.Knowledge discovery using genetic algorithm for maritime situational awareness[J].Expert Systems with Applications,2014,41(6):2742-2753.
  • 6Saad F,Nürnberger A.Overview of prior-art cross-lingual information retrieval approaches[J].World Patent Information,2012,34(4):304-314.
  • 7Pera M S,Qumsiyeh R,Ng Yiukai.Web-based closed-domain data extraction on online advertisements[J].Information Systems,2013,38(2):183-197.
  • 8Chmielewski M R,Grzymala-Busse J.Global discretization of continuous attributes as preprocessing for machine learning[J].International Journal of Approximate Reasoning,1996,15(4):319-331.
  • 9Janicke H,Wiebel A,Scheuermann G.Multifield visualization using local statistical of electronics[J].IEEE Trans on Visualization & Computer Graphics,2007,13(6):1384-1391.
  • 10Pawlak Z,Skowron A.Rough sets and Boolean reasoning[J].Information Sciences,2007,177(1):41-73.

引证文献2

二级引证文献6

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