WILLE R. Restructuring Lattice Theory: An Approach Based on Hierarchies of Concepts [C] //Ordered Sets. Dordrecht: Springer Netherlands, 1982: 445-470.
MA J M, CAI M J, ZOU C J. Concept Acquisition Approach of Object-Oriented Concept Lattices [J]. International Journal of Machine Learning and Cybernetics, 2017, 8(1): 123-134. doi: 10.1007/s13042-016-0576-1
WAN Q, WEI L. Approximate Concepts Acquisition Based on Formal Contexts [J]. Knowledge-Based Systems, 2015, 75: 78-86. doi: 10.1016/j.knosys.2014.11.020
CUI H, DENG A S, CHANG C M, et al. Granule Description of Object (Attribute)-Oriented Linguistic Concept Lattice Based on Dominance Relation [J]. International Journal of Computational Intelligence Systems, 2021, 14(1): 701. doi: 10.2991/ijcis.d.201230.001
常瑜珠, 万青, 张娟娟. 基于直观图的(三支)近似概念获取研究[J]. 西南大学学报(自然科学版), 2024, 46(5): 51-66. doi: 10.13718/j.cnki.xdzk.2024.05.005
魏玲, 曹丽, 祁建军, 等. 形式概念分析中的概念约简与概念特征[J]. 中国科学: 信息科学, 2020, 50(12): 1817-1833.
CUI H, YUE G L, ZOU L, et al. Multiple Multidimensional Linguistic Reasoning Algorithm Based on Property-Oriented Linguistic Concept Lattice [J]. International Journal of Approximate Reasoning, 2021, 131: 80-92. doi: 10.1016/j.ijar.2020.11.006
VACCARIO G, MEDO M, WIDER N, et al. Quantifying and Suppressing Ranking Bias in A Large Citation Network [J]. Journal of Informetrics, 2017, 11(3): 766-782. doi: 10.1016/j.joi.2017.05.014
DONG Y C, ZHA Q B, ZHANG H J, et al. Consensus Reaching in Social Network Group Decision Making: Research Paradigms and Challenges [J]. Knowledge-Based Systems, 2018, 162: 3-13. doi: 10.1016/j.knosys.2018.06.036
毛华, 刘畅, 袁晓垒, 等. 基于概念格层面的知识提取方法及应用[J]. 华中科技大学学报(自然科学版), 2024, 52(11): 37-42, 92.
沙立伟, 杨政, 刘红平, 等. 基于异构网络语言形式背景的知识发现及规则提取[J]. 模式识别与人工智能, 2024, 37(5): 469-478.
HUANG Y Y, LI T R, LUO C, et al. Matrix-Based Dynamic Updating Rough Fuzzy Approximations for Data Mining [J]. Knowledge-Based Systems, 2017, 119: 273-283. doi: 10.1016/j.knosys.2016.12.015
NGUYEN L T T, NGUYEN N T, VO B, et al. Efficient Method for Updating Class Association Rules in Dynamic Datasets with Record Deletion [J]. Applied Intelligence, 2018, 48(6): 1491-1505. doi: 10.1007/s10489-017-1023-z
ZHAO Z Y, LI C, ZHANG X J, et al. An Incremental Method to Detect Communities in Dynamic Evolving Social Networks [J]. Knowledge-Based Systems, 2019, 163: 404-415. doi: 10.1016/j.knosys.2018.09.002
任永功, 王玉玲, 刘洋, 等. 基于用户相关性的动态网络媒体数据无监督特征选择算法[J]. 计算机学报, 2018, 41(7): 1517-1535.
LI T S, ZHANG J W, YU P S, et al. Deep Dynamic Network Embedding for Link Prediction [J]. IEEE Access, 2018, 6: 29219-29230. doi: 10.1109/ACCESS.2018.2839770
YU B, LU B, ZHANG C, et al. Node Proximity Preserved Dynamic Network Embedding via Matrix Perturbation [J]. Knowledge-Based Systems, 2020, 196: 105822. doi: 10.1016/j.knosys.2020.105822
魏会廷, 陈永光. 面向社交网络重要信息传播的重叠节点挖掘模型研究[J]. 西南大学学报(自然科学版), 2024, 46(2): 150-158. doi: 10.13718/j.cnki.xdzk.2024.02.015
曹燕, 董一鸿, 邬少清, 等. 动态网络表示学习研究进展[J]. 电子学报, 2020, 48(10): 2047-2059.
LI D Y, ZHONG X X, DOU Z F, et al. Detecting Dynamic Community by Fusing Network Embedding and Nonnegative Matrix Factorization [J]. Knowledge-Based Systems, 2021, 221: 106961. doi: 10.1016/j.knosys.2021.106961
刘琳岚, 冯振兴, 舒坚. 基于时序图卷积的动态网络链路预测[J]. 计算机研究与发展, 2024, 61(2): 518-528.
马娜, 范敏, 李金海. 复杂网络下的概念认知学习[J]. 南京大学学报(自然科学), 2019, 55(4): 609-623.
刘文星, 范敏, 李金海. 网络形式背景下的社区划分方法研究[J]. 计算机科学与探索, 2021, 15(8): 1441-1449.
王玙, 刘东苏. 基于PageRank的动态网络核心节点检测及演化分析[J]. 情报学报, 2018, 37(7): 703-711.
郝宵荣, 王莉, 廉涛. 基于节点表示和子图结构的动态网络链接预测[J]. 模式识别与人工智能, 2021, 34(2): 117-126.
YAO L, WANG L N, PAN L, et al. Link Prediction Based on Common-Neighbors for Dynamic Social Network [J]. Procedia Computer Science, 2016, 83: 82-89. doi: 10.1016/j.procs.2016.04.102
毕崇武, 叶光辉, 彭泽, 等. 引文内容视角下的引文网络知识流动效应研究[J]. 情报科学, 2022, 40(2): 49-58.
蒋馨剑, 周艳波. 融合引用网络结构和时间特性的学术评价算法[J]. 小型微型计算机系统, 2023, 44(5): 1095-1101.
霍朝光, 但婷婷, 罗飞, 等. 基于图神经网络的跨学科引文推荐方法研究[J/OL]. 情报理论与实践, (2025-03-18) [2025-05-16]. https://link.cnki.net/urlid/11.1762.G3.20250318.0942.002.
徐伟华, 李金海, 魏玲, 等. 形式概念分析理论与应用[M]. 北京: 科学出版社, 2016.