Computer Science ›› 2018, Vol. 45 ›› Issue (1): 73-78.doi: 10.11896/j.issn.1002-137X.2018.01.011

Previous Articles     Next Articles

Attribute Reduction of Partially-known Formal Concept Lattices for Incomplete Contexts

WANG Zhen and WEI Ling   

  • Online:2018-01-15 Published:2018-11-13

Abstract: Partially-known formal concept,which was proposed recently,lays the foundation of data analysis of incomplete contexts and also provides the thought of studying on attribute reduction.This paper firstly proposed four kinds of attribute reduction:partially-known formal concept lattice reduction,meet(join)-irreducible elements preserving reduction and partially-known object formal concept preserving reduction.And then,it discussed the relationships among the four kinds of reduction.Finally,it presented the approaches to finding these reduction by discernibility matrices and discernibility functions.

Key words: Incomplete context,Partially-known formal concept,Attribute reduction,Discernibility matrix

[1] WILLE R.Restructuring Lattice Theory:An Approach Based on Hierarchies of Concepts[M]∥Riaral I,ed.ordered Sets.Reidel,Dord recht,1982:445-470.
[2] LIU X L,HONG W X,ZHANG T.TCM Differentiation Visua-lization Methods Based on Formal Concept Analysis[J].Journal of Yanshan University,2010,34(2):162-168.(in Chinese) 刘旭龙,洪文学,张涛.基于形式概念分析的中医辨证可视化方法[J].燕山大学学报,2010,34(2):162-168.
[3] MISSAOUI R,GODIN R.Extracting Exact and ApproximateRules from Databases [C]∥Proceedings of SOFTEKS Workshop on Incompleteness and Uncertainty in Information Systems.1993:209-222.
[4] GUO X E,WANG J H.Multi-dimensional Concept Lattice and Association Rules Discovery[J].Journal of Computer Application,2010,30(4):1072-1075.(in Chinese) 郭显娥,王俊红.多维概念格与关联规则的发现[J].计算机应用,2010,30(4):1072-1075.
[5] SUTTON A,MALETIC J I.Recovering UML Class Modelsfrom C++:A Detailed Explanation[J].Information and Software Technology,2007,49(3):212-229.
[6] GODIN R,MISSAOUI R.An Incremental Concept FormationApproach for Learning from Database[J].Theoretical Computer Science,1994,133(2):387-419.
[7] FREEMAN L,WHITE D.Using Galois Lattices to Represent Network Data[J].Sociological Methodology,1993,23:127-146.
[8] HO T B.An Approach to Concept Formation Based on Formal Concept Analysis[J].IEICE Transactions on Information and Systems,1995,E78-D(5):553-559.
[9] PAWLAK Z.Theoretical Aspects of Reasoning about Data[M].Boston,Kluwer Academic Publishers,1991.
[10] WEI L.The Theory and Methods of Rough Sets and Concept Lattice Reduction[D].Xi’an:Xi’an Jiaotong University,2005.(in Chinese) 魏玲.粗糙集与概念格约简理论与方法[D].西安:西安交通大学,2005.
[11] NOURINE L,RAYNAUD O.A Fast Algorithm for BuildingLattices[J].Information Processing Letters,1999,71:199-204.
[12] ZHANG W X,QIU G F.Uncertain Decision Making Based on Rough Sets[M].Beijing:Tsinghua University Press,2005:185-193.(in Chinese) 张文修,仇国芳.基于粗糙集的不确定决策[M].北京:清华大学出版社,2005:185-193.
[13] WEI L,WAN Q,QIAN T,et al(1)An Overview of Triadic Concept Analysis[J].Journal of Northwest University (Natural Science Edition),2014,44(5):689-699.(in Chinese) 魏玲,万青,钱婷,等.三元概念分析综述[J].西北大学学报(自然科学版),2014,44(5):689-699.
[14] REN R S,WEI L.The attribute reductions of three-way concept lattices[J].Knowledge-Based Systems,2016,99(C):92-102.
[15] BURMEISTER P,HOLZER R.On the treatment of incomplete knowledge in formal concept analysis[C]∥Conceptual Structures:Logical,Linguist,and Computa-tional Issues.Berlin,Heidelberg:Springer-Verlag,2000:385-398.
[16] LI J H,MEI C L,LV Y J.Incomplete decision contexts:Approximate concept construction,rule acquisition and knowledge reduction[J].International Journal of Approximate Reasoning,2013,54(1):149-165.
[17] YAO Y.Interval sets and three-way concept analysis in incomplete contexts[J].International Journal of Machine Learning & Cybernetics,2017,8(1):3-20.
[18] LI M Z,WANG G Y.Approximate concept construction with three-way decisions and attribute reduction in incomplete contexts[J].Knowledge-Based Systems,2016,91:165-178.
[19] DAVEY B A,PRIESTLEY H A.Introduction of Lattice and Order[M]∥Cambridge University Press.Cambridge United Kingdom,1990.
[20] ZHANG W X,WEI L,QI J J.Attribute reduction theory and approach to concept lattice[J].Science in China Series ,2005,48(6):713-726.

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
[1] LEI Li-hui and WANG Jing. Parallelization of LTL Model Checking Based on Possibility Measure[J]. Computer Science, 2018, 45(4): 71 -75 .
[2] SUN Qi, JIN Yan, HE Kun and XU Ling-xuan. Hybrid Evolutionary Algorithm for Solving Mixed Capacitated General Routing Problem[J]. Computer Science, 2018, 45(4): 76 -82 .
[3] ZHANG Jia-nan and XIAO Ming-yu. Approximation Algorithm for Weighted Mixed Domination Problem[J]. Computer Science, 2018, 45(4): 83 -88 .
[4] WU Jian-hui, HUANG Zhong-xiang, LI Wu, WU Jian-hui, PENG Xin and ZHANG Sheng. Robustness Optimization of Sequence Decision in Urban Road Construction[J]. Computer Science, 2018, 45(4): 89 -93 .
[5] SHI Wen-jun, WU Ji-gang and LUO Yu-chun. Fast and Efficient Scheduling Algorithms for Mobile Cloud Offloading[J]. Computer Science, 2018, 45(4): 94 -99 .
[6] ZHOU Yan-ping and YE Qiao-lin. L1-norm Distance Based Least Squares Twin Support Vector Machine[J]. Computer Science, 2018, 45(4): 100 -105 .
[7] LIU Bo-yi, TANG Xiang-yan and CHENG Jie-ren. Recognition Method for Corn Borer Based on Templates Matching in Muliple Growth Periods[J]. Computer Science, 2018, 45(4): 106 -111 .
[8] GENG Hai-jun, SHI Xin-gang, WANG Zhi-liang, YIN Xia and YIN Shao-ping. Energy-efficient Intra-domain Routing Algorithm Based on Directed Acyclic Graph[J]. Computer Science, 2018, 45(4): 112 -116 .
[9] CUI Qiong, LI Jian-hua, WANG Hong and NAN Ming-li. Resilience Analysis Model of Networked Command Information System Based on Node Repairability[J]. Computer Science, 2018, 45(4): 117 -121 .
[10] WANG Zhen-chao, HOU Huan-huan and LIAN Rui. Path Optimization Scheme for Restraining Degree of Disorder in CMT[J]. Computer Science, 2018, 45(4): 122 -125 .