计算机科学 ›› 2026, Vol. 53 ›› Issue (9): 157-164.doi: 10.11896/jsjkx.260600026
赵世澄1, 米据生1,2
ZHAO Shicheng1, MI Jusheng1,2
摘要: 概念约简是形式概念分析的核心环节,其目的是在减少概念格中概念的个数的同时保留全部原始信息。三支概念格作为三支决策理论与经典概念格的融合形式,其约简任务与经典场景存在显著差异:经典概念约简聚焦单一正信息的结构保留,而三支概念约简需同时兼顾正、负及不确定三类知识的完整性,判定标准更为严苛,结果更适配复杂决策场景下对多维度知识的保留需求。当前,针对三支概念格的概念约简的研究仍较为匮乏,缺乏高效可行的约简方法。针对这一问题,提出一种基于全局相关性与冗余性的OE概念约简框架。该框架融合OE概念的相关性与冗余性分析,构建一种优化的OE概念约简方法,可在保障三支知识结构完整性的前提下,有效识别并剔除冗余概念,得到保留二元关系的OE概念约简结果。实验结果表明,相较于现有OE概念约简方法,该方法在约简计算效率上具有显著优势,可有效提升OE概念约简的处理性能,为OE概念格理论发展及其在复杂决策分析中的应用提供新的支撑。
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| [1] PAWLAK Z.Rough sets[J].International Journal of Computer and Information Sciences,1982,11(5):341-356. [2] WEI L,CAO L,QI J J,et al.Concept reduction and conceptcharacteristics in formal concept analysis[J].Scientia Sinica Informationis,2020,50(12):1817-1833. [3] XIE X X,LI J J,CHEN D X,et al.Concept reduction preserving binary relation based on Boolean matrix[J].Journal of Shandong University:Natural Science,2020,55(5):32-45. [4] WANG X,PENG Z H,LI J Y,et al.A concept reduction method based on concept discernibility matrix[J].Computer Science,2021,48(1):125-130. [5] ZHAO S Y,QI J J,LI J N,et al.Concept reduction in formal concept analysis based on representative concept matrix[J].International Journal of Machine Learning and Cybernetics,2023,14(4):1147-1160. [6] LIU J,MI J S,LI Z L,et al.Dual three-way concept lattice and concept reduction based on concept composition[J].Computer Science,2023,50(6):122-130. [7] LI Y,ZHAO S Y,REN R S,et al.Concept reduction preserving antecedent information of rules[J].Journal of Northwest University:Natural Science Edition,2023,53(5):803-811. [8] WEI L,ZHAO S Y,QI J J.Symmetric formal context and itsconcept reduction[J].Journal of Northwest University:Natural Science Edition,2023,53(5):794-802. [9] LI X,ZHANG Q,WEI L.Relationship between triadic concept reduction and concept reduction[J].Computer Science,2025,52(6):151-158. [10] LI W,LI T R,QIAN Y H.Concept reduction via global rele-vance and redundancy viewpoints[J].Knowledge-Based Systems,2016,107:158-170. [11] YAO Y Y.An outline of a theory of three-way decisions[C] //Rough Sets and Current Trends in Computing.Berlin:Springer,2012:1-17. [12] QI J J,WEI L,YAO Y Y.Three-way formal concept analysis[C] //Rough Sets and Knowledge Technology.Cham:Springer,2014:732-741. [13] 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. [14] QI J J,QIAN T,WEI L.The connections between three-way and classical concept lattices[J].Knowledge-Based Systems,2016,91:143-151. [15] REN R,WEI L.The attribute reductions of three-way concept lattices[J].Knowledge-Based Systems,2016,99:92-102. [16] GAO X W,LIU G L,XIE Y H.Concept reduction of object-induced three-way concept lattices[C] //Lecture Notes in Computer Science.Cham:Springer,2022:265-273. [17] XIE J,YANG J,LI J,et al.Three-way concept lattice construction and association rule acquisition[J].Information Sciences,2025,701:121867. [18] WU W Z,LEUNG Y,MI J S.Granular computing and know-ledge reduction in formal contexts[J].IEEE Transactions on Knowledge and Data Engineering,2009,21(10):1461-1474. [19] CHANG X X,QIN K Y.Granular reduction method of formal context based on object-induced three-way concept lattice[J].Computer Science,2018,45(10):225-228. [20] WANG Z,SHI C J,YAO Y Y.Tri-granularity attribute reduction of three-way concept lattices[J].Knowledge-Based Systems,2023,276:110762. |
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