[1]MAO Hua,XU Dehua,LIU Chuan,et al.Knowledge representation and extraction method of partially-known fuzzy semiconcepts[J].CAAI Transactions on Intelligent Systems,2024,19(4):1016-1026.[doi:10.11992/tis.202304057]
Copy
Knowledge representation and extraction method of partially-known fuzzy semiconcepts
CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume:
19
Number of periods:
2024 4
Page number:
1016-1026
Column:
学术论文—人工智能基础
Public date:
2024-07-05
- Title:
- Knowledge representation and extraction method of partially-known fuzzy semiconcepts
- Keywords:
- fuzzy formal context; semiconcept; interval set; interval-set concept; partially-known formal concept; fuzzy concept; partially-known fuzzy semiconcept; knowledge representation and extraction
- CLC:
- TP18
- DOI:
- 10.11992/tis.202304057
- Abstract:
- To ensure that the extraction of uncertain information expressed in the form of "intervals" is focused, it is necessary to extract the corresponding attribute (object) interval set for the object (attribute) set. By introducing two thresholds from the fuzzy context, the unilateral interval set is combined with the classical semiconcept to extract the corresponding object (attribute) interval set for the attribute(object) set, and thereby the interval set extent-set intent(set extent-interval set intent)(ISE-SI (SE-ISI)) type partially-known fuzzy semiconcept is proposed. All ISE-SI (SE-ISI) type partially-known fuzzy semiconcepts form a lattice, and the algorithm based on lattice search for all ISE-SI (SE-ISI) type partially-known fuzzy semiconcepts is given. The multiple advantages of these two knowledge representation forms are demonstrated by comparing them with existing achievements. The results obtained in this paper have the advantages of broad applicability and strong practical application in knowledge representation and extraction methods.
- References:
-
[1] WILLE R. Restructuring lattice theory: an approach based on hierarchies of concepts[M]Dordrecht: Springer, 1982: 445- 470.
[2] GANTER B, WILLE R. Formal concept analysis: mathe- matical foundations[M]. Berlin: Springer, 1999: 78-98.
[3] 毛华, 武秀. 三支概念的一种构建方法[J]. 智能系统学报, 2020, 15(3): 514–519
MAO Hua, WU Xiu. A new method for constructing three-way concept[J]. CAAI transactions on intelligent systems, 2020, 15(3): 514–519
[4] WANG Shengwen, LI Qingguo. A representation of L-domain by formal concept analysis[J]. Soft computing, 2022, 26(19): 9751–9760.
[5] 姬儒雅, 魏玲, 任睿思, 等. 毕达哥拉斯模糊三支概念格[J]. 山东大学学报(理学版), 2020, 55(11): 58–65
JI Ruya, WEI Ling, REN Ruisi, et al. Pythagorean fuzzy three-way concept lattice[J]. Journal of Shandong Univ- ersity (natural science edition), 2020, 55(11): 58–65
[6] 王太滨, 李德玉, 翟岩慧. 覆盖多粒度下的形式概念更新方法[J]. 计算机科学, 2023, 50(10): 18–27
WANG Taibin, LI Deyu, ZHAI Yanhui. Method of updating formal concept under covering multi-granularity[J]. Computer science, 2023, 50(10): 18–27
[7] YANG Dongqiang, YANG Xinran, JIA Hui, et al. Construction of fuzzy linguistic approximate concept lattice in an incomplete fuzzy linguistic formal context[J]. International journal of computational intelligence systems, 2022, 15(1): 154–169.
[8] SHEMIS E, AMMAR M. A comprehensive review on updating concept lattices and its application in updating association rules[J]. Data mining and knowledge discovery, 2021, 11(2): 1–25.
[9] 陈曜琦, 徐伟华, 蒋宗颖. 三支概念的恢复集[J]. 山东大学学报(理学版), 2023, 58(12): 52–62
CHEN Yaoqi, XU Weihua, JIANG Zongying. Recovery set of three-way concept[J]. Journal of Shandong University (natural science edition), 2023, 58(12): 52–62
[10] 魏玲, 赵思雨, 祁建军. 对称形式背景及其概念约简[J]. 西北大学学报(自然科学版), 2023, 53(5): 794–802
WEI Ling, ZHAO Siyu, QI Jianjun. Symmetric formal context and its concept reduct[J]. Journal of Northwest University (natural science edition), 2023, 53(5): 794–802
[11] 马文胜, 侯锡林. 形式概念分析中的同效关系与概念约简[J]. 计算机科学, 2023, 50(4): 63–76
MA Wensheng, HOU Xilin. Same effect relation and concept reduction in formal concept analysis[J]. Computer science, 2023, 50(4): 63–76
[12] LONG Binghan, XU Weihua, ZHANG Xiaoyan. Double threshold construction method for attribute-induced three- way concept lattice in incomplete fuzzy formal context[J]. The journal of engineering, 2020(13): 549–554.
[13] ZHI Huilai, LI Jinhai. Granule description of incomplete data: a cognitive viewpoint[J]. Cognitive computation, 2022, 14: 2108–2119.
[14] ZHI Huilai, LI Jinhai. Granule description based knowledge discovery from incomplete formal contexts via necessary attribute analysis[J]. Information sciences, 2019, 485: 347–361.
[15] 胡明涵, 张俐, 任飞亮. 模糊形式概念分析与模糊概念格[J]. 东北大学学报(自然科学版), 2007, 28(9): 1274–1277
HU Minghan, ZHANG Li, REN Feiliang. Fuzzy formal concept analysis and fuzzy concept lattices[J]. Journal of Northeastern University(natural science edtion), 2007, 28(9): 1274–1277
[16] SHAO Mingwen, LEUNG Yee, WANG Xizhao, et al. Granular reducts of formal fuzzy contexts[J]. Knowledge-based systems, 2016, 114(15): 156–166.
[17] YAO Yiyu. Interval-set algebra for qualitative knowledge representation[C]//Procedding of ICCI’93: 5th International Conference on Computing and Information. Sudbury: IEEE, 1993: 370-374.
[18] PAWLAK Z. Rough sets[J]. International journal of com- puter and information science, 1982, 11: 341–356.
[19] 梁美社, 米据生, 张少谱. 双论域上的广义直觉模糊概率粗糙集模型及其应用[J]. 智能系统学报, 2022, 17(3): 585–592
LIANG Meishe, MI Jusheng, ZHANG Shaopu. Generali- zed intuitionistic fuzzy probabilistic rough set models on two universes and their applications[J]. CAAI transact- ions on intelligent systems, 2022, 17(3): 585–592
[20] 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: 69-88.
XU Weihua, LI Jinhai, WEI Ling, et al. Formal concept analysis: theory and application[M]. Beijing: Science Pre- ss, 2016: 69-88.
[21] MA Jianmin, CAI Mingjie. Concept acquisition approach of object-oriented concept lattices[J]. International journal of machine learning and cybernetics, 2017, 8(1): 123–134.
[22] 郭庆春, 马建敏. 对偶区间集概念格上区间集协调集的判定方法[J]. 计算机科学, 2020, 47(3): 98–102
GUO Qingchun, MA Jianmin. Judgment methods of interval-set consistent sets of dual interval-set concept lattices[J]. Computer science, 2020, 47(3): 98–102
[23] 马建敏, 胡玲玲. 决策形式背景上区间集概念格的属性约简[J]. 模式识别与人工智能, 2018, 31(7): 581–590
MA Jianmin, HU Lingling. Attribute reductions of interval-Set concept lattices for decision formal contexts[J]. Pattern recognition and artificial intelligence, 2018, 31(7): 581–590
[24] REN Ruisi, WEI Ling, YAO Yiyu. An analysis of three types of partially-known formal concepts[J]. International journal of machine learning and cybernetics, 2018, 9: 1767–1783.
[25] YAO Yiyu. Interval sets and three-way concept analysis in incomplete contexts[J]. International journal of machine learning and cybernetics, 2017, 8: 3–20.
[26] 王振, 魏玲. 基于单边区间集概念格的不完备形式背景的属性约简[J]. 计算机科学, 2018, 45(1): 73–78
WANG Zhen, WEI Ling. Attribute reduction of partially- known formal concept lattices for incomplete contexts[J]. Computer science, 2018, 45(1): 73–78
[27] MAO Hua, LIU Xiaoqin, WANG Gang. Two forms of three-way semiconcepts[J]. Journal of intelligent and fuzzy systems, 2021, 40(6): 10853–10864.
[28] VORMBROCK B, WILLE R. Semiconcept and proto- concept algebras: the basic theorems[M]. Berlin: Springer, 2005: 34-48.
[29] 毛华, 牛振华, 马经泽, 等. 基于模糊三支区间集半概念知识提取方法研究[J]. 郑州大学学报(理学版), 2024, 56(1): 81–87
MAO Hua, NIU Zhenhua, MA Jingze, et al. Research on knowledge extraction method based on fuzzy three-way interval-Set semiconcept[J]. Journal of Zhengzhou University (natural science edition), 2024, 56(1): 81–87
[30] 毛华, 马经泽, 牛振华, 等. 三支半概念的广义结构及粗糙集近似算子[J]. 模糊系统与数学, 2022, 36(6): 89–101
MAO Hua, MA Jingze, NIU Zhenhua, et al. Generalized structures and rough set approximation operators of three- way semiconcepts[J]. Fuzzy systems and mathematics, 2022, 36(6): 89–101
- Similar References:
Memo
-
Last Update:
1900-01-01