Computer Science ›› 2023, Vol. 50 ›› Issue (6): 109-115.doi: 10.11896/jsjkx.220900111

• Granular Computing & Knowledge Discovery • Previous Articles     Next Articles

Boolean Matrix Representation of Triadic Concepts

WANG Xia, LI Junyu, WU Weizhi   

  1. School of Information Engineering,Zhejiang Ocean University,Zhoushan,Zhejiang 316022,China
    Key Laboratory of Oceanographic Big Data Mining and Application of Zhejiang Province(Zhejiang Ocean University),Zhoushan,Zhejiang 316022,China
  • Received:2022-09-11 Revised:2023-03-22 Online:2023-06-15 Published:2023-06-06
  • About author:WANG Xia,born in 1980,Ph.D,asso-ciate professor,is a member of China Computer Federation.Her main research interests include formal concept analysis,rough set theory,and granular computing.LI Junyu,born in 1979,Ph.D,associate professor.His main research interests include formal concept analysis and rough set theory.
  • Supported by:
    National Natural Science Foundation of China(61573321,41631179,61773349) and Natural Science Foundation of Zhejiang Province,China(LY18F030017).

Abstract: The Boolean matrix method is introduced into triadic concept analysis to study the Boolean matrix representation me-thod of triadic context and triadic concept.Firstly,the relation matrix of triadic context is defined.The triadic context under each condition is regarded as a Boolean matrix,then the triadic context is a Boolean block matrix,which is the relation matrix of triadic context.Next,the Boolean matrix representation method of induced operators on triadic context is investigated by using the relation matrix.Then,the Boolean matrix representation method of the extent,intent and modus of a triadic concept is obtained.This method only uses some basic Boolean matrix operations when generating triadic concepts,and does not involve the induced operator of triadic context.Finally,the Boolean matrix representation methods are given according to enumeration method of triadic concept construction and triadic concept construction based on object-conditional triadic concepts respectively.Triadic contexts and triadic concepts are explored from the viewpoint of matrix based on the Boolean matrix representation method of triadic concepts,which gives a new perspective to study triadic concept analysis.

Key words: Triadic concept analysis, Triadic context, Triadic concept, Induced operator, Boolean matrix

CLC Number: 

  • TP301
[1]WILLE R.Restructuring lattice theory:An approach based onhierarchies of concepts [G]//Ordered Sets.Dordrecht:Reidel,1982:445-470.
[2]GANTER B,WILLE R.Formal Concept Analysis:Mathematical Foundations [M]//Berlin:Springer,1999:17-61.
[3]ZHANG Q X.The judgment method of consistent sets in decision formal context based on Boolean matrix[J].Journal of Zhangzhou Normal University (Natural Sciences),2012,25(1):22-25.
[4]LI T J,WANG X,XU Y H.Boolean computation approach of formal concepts[J].Journal of Nanjing University(Natural Sciences),2013,49(5):553-560.
[5]SHI H,WEI L.Boolean expression of object (property)-oriented concept lattice[J].Journal of Nanjing University (Natural Sciences),2015,51(2):415-420.
[6]SHAO M W,LIU M,GUO L.Vector-based attribute reduction method for formal contexts[J].Fundamenta Informaticae,2013,126(4):397-414.
[7]SHI H.Boolean expression and attriute reduction of object(property)-oriented concept lattice [D].Xi'an:Northwest University,2015.
[8]WANG D L.Attribute reduction for concept lattice with matrix[J].Computer Applications,2009,31(6):28-32.
[9]WANG D L.Knowledge reduction algorithm based on elementaryrow transformation of Boolean matrix[J].Computer Applications,2007(9):2267-2269.
[10]WAN Q,MA Y C,YANG X F.The reduction of formal context based on Boolean matrix[J].Basic Sciences Journal of Textile Universities,2019,32(1):67-72.
[11]ZHANG C L,LI J J,LIN Y D.Matrix-type attribute reduction for inconsistent formal decision contextS[J].Journal of Frontiers of Computer Science and Technology,2020,14(3):534-540.
[12]ZHANG C L.Research on matrix approach to attribute reduction in concept lattice model [D].Zhangzhou:Minnan Normal University,2021.
[13]LIN Y D,LI J J,ZHANG C L.Attribute reductions of fuzzy-crisp concept lattices based on matrix[J].Pattern Recognition and Artificial Intelligence,2020,33(1):21-31.
[14]HUAND Q.Attribute reduction approach to an ordered information system based on boolean matrix [D].Xi'an:Northwest University,2016.
[15]ZHANG Q X.Attribute reduction method for concept lattice based on Boolean matrices [D].Zhangzhou:Zhangzhou Normal University,2012.
[16]TRNECKA M,VYJIDACEK R.Revisiting the GreCon algorithm for Boolean matrix factorization[C]//Proceedings of the 15th International Conference on Concept Lattices and Their Applications.2020:59-70.
[17]TRNECKA M,TRNECKOVA M.Data reduction for boolean matrix factorization algorithms based on formal concept analysis[J].Knowledge-Based Systems,2018,158:75-80.
[18]LEHMANN F,WILLE R.A triadic approach to formal concept analysis[C]//Proceeding of the 3rd International Conference on Conceptual Structures Applications,Implementation and Theory.Berlin:Springer,1995:32-43.
[19]WILLE R.The basic theorem of triadic concept analysis[J].Order,1995,12(2):149-158.
[20]BIEDERMANN K.Triadic Galois connections [G]//General Algebra and Applications in Discrete Mathematics.Aachen:ShakerVerlag,1997:23-33.
[21]BIEDERMANN K.An equational theory for trilattices[J].Algebra Universalis,1999,42(4):253-268.
[22]GROH B,WILLE R.Lattices of triadic concept graphs[C]//Proceeding of the 8th International Conference on Conceptual Structures.Berlin:Springer,2000:332-341.
[23]BIEDERMANN K.How triadic diagrams represent conceptualstructures[C]//Proceeding of the 5th International Conference on Conceptual Structures Fulfilling Peirce's Dream.Berlin:Springer,1997:304-317.
[24]GANTER B,OBIEDKOV S A.Implications in triadic formalcontexts[C]//Proceeding of the 12th International Conference on Conceptual Structures.Berlin:Springer,2004:186-195.
[25]MISSAOUI R,KWUIDA L.Mining triadic association rulesfrom ternary relations[C]//Proceeding of the 9th International Conference on Formal Concept Analysis.Berlin:Springer,2011:204-218.
[26]DAU F,WILLE R.On the modal understanding of triadic context [G]//Classification and Information Processing at the Turn of the Millennium.Berlin:Springer,2000:83-94.
[27]JASCHKE R,HOTHO A,SCHMITZ C,et al.TRIAS-an algorithm for mining iceberg trilattices[C]//Proceeding of the 6th International Conference on Data Mining.Piscataway,NJ:IEEE,2006:907-911.
[28]KAVTOUE M,KUZNETSOV S,MACKO J,et al.Minging biclusters of similar values with triadic concept analysis[C]//Proceeding of the 8th International Conference on Concept Lattices and Their Applications.Berlin:Springer,2011:175-190.
[29]KAYTOUE M,KUZNETSOV S O,MACKO J,et al.Bicluste-ring meets triadic concept analysis[J].Annals of Mathematics and Artificial Intelligence,2014,70(1/2):55-79.
[30]BELOHLAVEK R,VYCHODIL V.Optimal factorization ofthree-way binary data[C]//Proceeding of 2010 IEEE International Conference on Granular Computing.Piscataway,NJ:IEEE,2010:61-66.
[31]GLODEANU C.Factorization methods of binary,triadic,realand fuzzy data[J].Studia Universitatis Babes-Bolyai Series Informatica,2011,56 (2):81-86.
[32]BELOHLAVEK R,GLODEANU C,VYCHODIL V.Optimalfactorization of three-way binary data using triadic concepts[J].Order,2013,30(2):437-454.
[33]CYNTHIA G.Tri-ordinal factor analysis[C]//Proceeding of the 11th International Conference on Formal Concept Analysis.Berlin:Springer,2013:125-140.
[34]BELOHLAVEK R,OSICKA P.Triadic concept analysis of data with fuzzy attributes[C]//Proceeding of 2010 IEEE International Conference on Granular Computing.Piscataway,NJ:IEEE,2010:661-665.
[35]BELOHLAVEK R,OSICKA P.Triadic concept lattices of data with graded attributes[J].International Journal of General System,2012,41(2):93-108.
[36]KONECNY J,OSICAKA P.Triadic concept lattices in theframework of aggregation structures[J].Information Sciences,2014,279(1):512-527.
[37]GLODEANU C.Fuzzy-Valued triadic implications [C]//Proceeding of the 7th International Conference on Concept Lattices and Their Applications.2011:159-173.
[38]BELOHLAVEK R,OSICKA P.Triadic fuzzy Galois connections as ordinary connections[J].Fuzzy Sets and Systems,2014,249:83-99.
[39]TANG Y Q,FAN M,LI J H.Cognitive system model and approach to transformation of information granules under triadic formal concept analysis[J].Journal of Shandong University:Natural Science,2014,49(8):102-106.
[40]QI J J,WEI L.Simplification of triadic contexts and concept trilattices[J].Computer Science,2017,44(9):53-57.
[41]WANG X,ZHANG Q,LI J Y,et al.Triadic concept analysis based on rough set theory[J].Journal of Northwest University:Natural Science Edition,2017,52(7):37-43.
[42]KUMAR C A,MOULISWARAN S C,LI J H,et al.Role based access control design using triadic concept analysis[J].Journal of Central South University,2016,23(12):3183-3191.
[43]LI Z,ZHANG Z,WANG L M.Research text classification algorithm based on triadic concept analysis[J].Computer Science,2017,44(8):207-215.
[44]WANG X,JIANG SH,LI J Y,et al.A construction method of triadic concepts[J].Journal of Computer Research and Development,2019,56(4):844-853.
[45]WANG X,QUAN Y,LI J Y,et al.Incremental constructionmethod of triadic concepts[J].Journal of Nanjing University(Natural Sciences),2022,58(1):19-28.
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