Computer Science ›› 2018, Vol. 45 ›› Issue (10): 21-26.doi: 10.11896/j.issn.1002-137X.2018.10.004

• CGCKD 2018 • Previous Articles     Next Articles

Rules Acquisition on Three-way Class Contexts

REN Rui-si1, WEI Ling1, QI Jian-jun2   

  1. School of Mathematics,Northwest University,Xi’an 710127,China 1
    School of Computer Science & Technology,Xidian University,Xi’an 710071,China 2
  • Received:2018-04-17 Online:2018-11-05 Published:2018-11-05

Abstract: Rules acquisition is an important problem in three-way concept analysis.Based on attribute-induced three-way concepts,two kinds of three-way class contexts were defined,namely three-way condition class contexts and three-way decision class contexts.The class concepts in these two different three-way class contexts were defined and the structures of class concepts were studied.Moreover,the relationships between the class concepts in three-way decision class contexts and the attribute-induced three-way concepts in three-way weakly consistent formal decision contexts were discussed.Then the rules based on three-way decision class concepts were presented,and the way to acquire them was shown.Furthermore,compared to the rules acquired from the three-way weakly consistent formal decision contexts,the class context based rules were proved to be superior than three-way weakly consistent context based rules.Specifically,the number of class context based rules is smaller than the number of three-way weakly consistent context based rules,but for each three-way weakly consistent context based rule,there exists a class context based rule containing more know-ledge.Finally,considering the three-way condition class context,the reverse rules were defined.Considering both three-way condition class contexts and three-way decision class contexts,the double directed rules were presented.

Key words: Attribute-induced three-way concept, Three-way weakly consistent formal decision context, Three-way condition class context, Three-way decision class context, Rules acquisition

CLC Number: 

  • O29
[1]QI J J,WEI L,YAO Y Y.Three-way Formal Concept Analysis[C]∥International Conference on Rough Sets and Knowledge Technology.Cham:Springer,2014:732-741.
[2]QI J J,QIAN T,WEI L.The Connections Between Three-way and Classical Concept Lattices [J].Knowledge-Based Systems,2016,91(C):143-151.
[3]REN R S,WEI L.The Attribute Reductions of Three-way Concept Lattices [J].Knowledge-Based Systems,2016,99(C):92-102.
[4]YAO Y Y.An Outline of A Theory of Three-way Decisions[C]∥ Rough Sets and Current Trends in Computing.Springer Berlin Heidelberg,2012:1-17.
[5]WILLE R.Restructuring Lattice Theory:An Approach Based on Hierarchies of Concepts [C]∥Proceedings of the NATO Advanced Study Institute.Dordrecht:Springer Berlin Heidelberg,1982:445-470.
[6]GANTER B,WILLE R.Formal Concept Analysis:Mathematical Foundations [M].Berlin Heidelberg:Springer-Verlag,1999.
[7]YAO Y Y.Interval Sets and Three-way Concept Analysis in Incomplete context [J].International Journal of Machine Learning &Cybernetics,2017,8(1):3-20.
[8]REN R S,WEI L,YAO Y Y.An Analysis of Three Types of Partially-known Formal Concepts [J/OL].International Journal of Machine Learning & Cybernetics.
[10]LI J H,LV Y J.Attribute Reduction and Rules Extraction in Decision Formal Context based on Concept Lattice [J].Mathematics in Practice and Theory,2009,39(7):182-188.(in Chinese)
[11]LI 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):1096-1106.
[12]LI J H,WANG J H,MEI C L,et al.Weakly Closed Label Concept Lattice and Its Application to Rule Acquisition in Decision Formal Contexts [C]∥Proceedings of International Conference on Machine Learning and Cybernetics.Piscataway:IEEE,2013:658-663.
[13]LI T.Knowledge Acquisition in Formal Decision Context [D].Xi’an:Northwest University,2013.(in Chinese)
[14]ZHU Z C,WEI L.Two-way Rules Acquisition based on Class Contexts [J].Journal of Northwest University (Natural Science Edition),2015,45(4):517-524.(in Chinese)
[15]PREDIGER S.Formal Concept Analysis for General Objects [J].Discrete Applied Mathematics,2003,127(2):337-355.
[16]LIU L,QIAN T,WEI L.Rules Extraction in Formal Decision Contexts based on Attribute-induced Three-way Concept Lattices [J].Journal of Northwest University (Natural Science Edition),2016,46(4):481-487.(in Chinese)
[1] LI Zhong-ling, MI Ju-sheng, XIE Bin. Attribute Reduction in Inconsistent Decision Formal Contexts [J]. Computer Science, 2019, 46(12): 257-260.
Full text



[1] . [J]. Computer Science, 2018, 1(1): 1 .
[2] LEI Li-hui and WANG Jing. Parallelization of LTL Model Checking Based on Possibility Measure[J]. Computer Science, 2018, 45(4): 71 -75 .
[3] 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 .
[4] ZHANG Jia-nan and XIAO Ming-yu. Approximation Algorithm for Weighted Mixed Domination Problem[J]. Computer Science, 2018, 45(4): 83 -88 .
[5] 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 .
[6] 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 .
[7] 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 .
[8] 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 .
[9] 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 .
[10] 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 .