Computer Science ›› 2023, Vol. 50 ›› Issue (10): 7-17.doi: 10.11896/jsjkx.230600037
• Granular Computing & Knowledge Discovery • Previous Articles Next Articles
NIU Lihui1, MI Jusheng1,2, BAI Yuzhang1
CLC Number:
[1]WILLE R.Restructuring lattice theory: An approach based on hierarchies of concepts[J].Ordered Sets,1982,83:445-470. [2]GANTER B,WILLE R.Formal concept analysis[M].Springer Berlin Heidelberg,1999. [3]WILLE R.Concept lattices and conceptual knowledge systems[J].Computers & Mathematics with Applications,1992,23(6/7/8/9):493-515. [4]WILLE R.Restructuring lattice theory: an approach based onhierarchies of concepts[J].Lecture Notes in Computer Science,2009,5548(1):314-339. [5]WEI L,QI J J,ZHANG W X.Attribute reduction theory of concept lattice based on decision formal contexts[J].Science in China Series F:Information Sciences,2008,51(7):910-923. [6]QUAN T T,NGO L N,HUI S C.An effective clustering-basedapproach for conceptual association rules mining[C]//IEEE-RIVF International Conference on Computing and Communication Technologies.IEEE,2009:1-7. [7]RICHARDS D,MALIK U.Multi-level knowledge discoveryfrom rule bases[J].Applied Artificial Intelligence,2003,17(3):181-205. [8]WILLE R.Why can concept lattices support knowledge disco-very in databases?[J].Journal of Experimental & Theoretical Artificial Intelligence,2002,14(2/3):81-92. [9]ZHAO Y X,LI J H,LIU W Q,et al.Cognitive concept learning from incomplete information[J].International Journal of Machine Learning and Cybernetics,2017,8(1):159-170. [10]ZHI H L,LI J H.Granule description based knowledge disco-very from incomplete formal contexts via necessary attribute analysis[J].Information Sciences,2019,485:347-361. [11]CARPINETO C,ROMANO G.Exploiting the potential of concept lattices for information retrieval with CREDO[J].Journal of Universal Computer Science,2004,10(8):985-1013. [12]KUZNETSOV S O.Machine learning on the basis of formalconcept analysis[J].Automation and Remote Control,2001,62(10):1543-1564. [13]SAMPATH S,SPRENKLE S,GIBSON E,et al.Applying concept analysis to user-session-based testing of web applications[J].IEEE Transactions on Software Engineering,2007,33(10):643-658. [14]SNELTING G.Reengineering of configurations based on mathe-matical concept analysis[J].ACM Transactions on Software Engineering and Methodology,1996,5(2):146-189. [15]JAN K.On efficient factorization of standard fuzzy concept lattices and attribute-oriented fuzzy concept lattices[J].Fuzzy Sets &Systems,2018,351:108-121. [16]MAO H,ZHENG Z.The construction of fuzzy concept lattice based on weighted complete graph[J].Journal of Intelligent & Fuzzy Systems,2019,36(6):5797-5805. [17]QI J J,QIAN T,WEI L.The connections between three-way and classical concept lattices[J].Knowledge-Based Systems,2016,91:143-151. [18]QI J J,WEI L,REN R S.3-way concept analysis based on 3-va-lued formal contexts[J].Cognitive Computation,2021,14(6):1900-1912. [19]QI J J,WEI L,YAO Y Y.Three-way formal concept analysis[C]//International Conference on Rough Sets and Knowledge Technology.Springer,2014:732-741. [20]SHAO M W,LV M M,LI K W,et al.The construction of attribute (object)-oriented multi-granularity concept lattices[J].International Journal of Machine Learning and Cybernetics,2020,11(5):1017-1032. [21]BURMEISTER P,HOLZER R.On the treatment of incomplete knowledge in formal concept analysis[C]//International Confe-rence on Conceptual Structures.Springer,2000:385-398. [22]LI J H,MEI C L,LV Y J.Incomplete decision contexts:ap-proximate concept construction,rule acquisition and knowledge reduction[J].International Journal of Approximate Reasoning,2013,54(1):149-165. [23]LI J H,HUANG C C,MEI C L,et al.An intensive study on rule acquisition in formal decision contexts based on minimal closed label concept lattices[J].Intelligent Automation & Soft Computing,2017,23(3):519-533. [24]OBIEDKOV S.Modal logic for evaluating formulas in incom-plete contexts[C]//International Conference on Conceptual Structures.Springer,2002:314-325. [25]DUBOIS D,SAINT-CYR F,PRADE H.A possibility-theoretic view of formal concept analysis[J].Fundamenta Informaticae,2007,75(1/2/3/4):195-213. [26]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. [27]LI C P,LI J H,HE M.Concept lattice compression in incomplete contexts based on k-medoids clustering[J].International Journal of Machine Learning and Cybernetics,2016,7(4):539-552. [28]YAO Y Y.Interval sets and three-way concept analysis in incomplete contexts[J].International Journal of Machine Lear-ning and Cybernetics,2017,8(1):3-20. [29]REN R S,WEI L,YAO Y Y.An analysis of three types of partially-known formal concepts[J].International Journal of Machine Learning and Cybernetics,2018,9(11):1767-1783. [30]WANG Z,WEI L,QI J J,et al.Attribute reduction of SE-ISI concept lattices for incomplete contexts[J].Soft Computing,2020,24(20):15143-15158. [31]YANG D Q,YANG X R,JIA H,et al.Construction of fuzzy linguistic approximate concept lattice in an incomplete fuzzy linguistic formal context[J].International Journal of Computa-tional Intelligence Systems,2022,15(1):1-9. [32]REN Y,LI J H,KUMAR C A,et al.Rule acquisition in formal decision contexts based on formal,object-oriented and property-oriented concept lattices[J/OL].The Scientific World Journal,2014,2014:1-10.http://dx.doi.org/10.1155/2014/685362. [33]HU Q,QIN K Y,YANG H,et al.A novel approach to attribute reduction and rule acquisition of formal decision context[J/OL].https://doi.org/10.1007/s10489-022-04139-2. [34]WEI L,LIU L,QI J J,et al.Rules acquisition of formal decision contexts based on three-way concept lattices[J].Information Sciences,2020,516:529-544. [35]SHAO M W,LEUNG Y,WU W Z.Rule acquisition and complexity reduction in formal decision contexts[J].International Journal of Approximate Reasoning,2014,55(1):259-274. [36]ZHANG W X,WEI L,QI J J.Attribute reduction theory andapproach to concept lattice[J].Science in China Series F:Information Sciences,2005,48(6):713-726. [37]HE X L,LIU Z Y,QIAN T.Rule Acquisition of Property Oriented Concept Lattice Based on Three-Way Decision[J].Computer Engineering and Applications,2022,(19):152-157. |
[1] | XU Yi, LUO Fan, WANG Min. Three-way Decision Movement Strategy Based on Hierarchical Clustering [J]. Computer Science, 2023, 50(6): 92-99. |
[2] | SONG Faxing, MIAO Duoqian, ZHANG Hongyun. Semi-supervised Object Detection with Sequential Three-way Decision [J]. Computer Science, 2023, 50(10): 1-6. |
[3] | WANG Zhi-cheng, GAO Can, XING Jin-ming. Three-way Approximate Reduction Based on Positive Region [J]. Computer Science, 2022, 49(4): 168-173. |
[4] | MA Xin-yu, JIANG Chun-mao, HUANG Chun-mei. Optimal Scheduling of Cloud Task Based on Three-way Clustering [J]. Computer Science, 2022, 49(11A): 211100139-7. |
[5] | ZHANG Shi-peng, LI Yong-zhong. Intrusion Detection Method Based on Denoising Autoencoder and Three-way Decisions [J]. Computer Science, 2021, 48(9): 345-351. |
[6] | WANG Zheng, JIANG Chun-mao. Cloud Task Scheduling Algorithm Based on Three-way Decisions [J]. Computer Science, 2021, 48(6A): 420-426. |
[7] | XIN Xian-wei, SHI Chun-lei, HAN Yu-qi, XUE Zhan-ao, SONG Ji-hua. Incremental Tag Propagation Algorithm Based on Three-way Decision [J]. Computer Science, 2021, 48(11A): 102-105. |
[8] | LIANG Wei, DUAN Xiao-dong, XU Jian-feng. Three-way Filtering Algorithm of Basic Clustering Based on Differential Measurement [J]. Computer Science, 2021, 48(1): 136-144. |
[9] | XUE Zhan-ao, ZHANG Min, ZHAO Li-ping, LI Yong-xiang. Variable Three-way Decision Model of Multi-granulation Decision Rough Sets Under Set-pair Dominance Relation [J]. Computer Science, 2021, 48(1): 157-166. |
[10] | CHEN Yu-jin, XU Ji-hui, SHI Jia-hui, LIU Yu. Three-way Decision Models Based on Intuitionistic Hesitant Fuzzy Sets and Its Applications [J]. Computer Science, 2020, 47(8): 144-150. |
[11] | XIANG Wei, WANG Xin-wei. Imbalance Data Classification Based on Model of Multi-class Neighbourhood Three-way Decision [J]. Computer Science, 2020, 47(5): 103-109. |
[12] | LI Yan, ZHANG Li, CHEN Jun-fen. Attribute Reduction Method Based on Sequential Three-way Decisions in Dynamic Information Systems [J]. Computer Science, 2019, 46(6A): 120-123. |
[13] | XUE Zhan-ao, HAN Dan-jie, LV Min-jie, ZHAO Li-ping. New Three-way Decisions Model Based on Granularity Importance Degree [J]. Computer Science, 2019, 46(2): 236-241. |
[14] | LI Yan, ZHANG Li, WANG Xue-jing, CHEN Jun-fen. Attribute Reduction for Sequential Three-way Decisions Under Dominance-Equivalence Relations [J]. Computer Science, 2019, 46(2): 242-148. |
[15] | YAN An, YAN Xin-yi, CHEN Ze-hua. Formal Vector Method of Rule Extraction for Consistent Decision Information System [J]. Computer Science, 2019, 46(10): 236-241. |
|