[1]WANG Wen,KANG Xiangping,WU Yan.Knowledge acquisition model of concept lattice in an incomplete formal context[J].CAAI Transactions on Intelligent Systems,2019,14(5):1048-1055.[doi:10.11992/tis.201809021]
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Knowledge acquisition model of concept lattice in an incomplete formal context

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 14 Number of periods: 2019 5 Page number: 1048-1055 Column: 学术论文—知识工程 Public date: 2019-09-05
Title:
Knowledge acquisition model of concept lattice in an incomplete formal context
Author(s):
WANG Wen1; 2;  KANG Xiangping3; 4;  WU Yan2
1. Department of Automation, Taiyuan Industrial College, Taiyuan 030008, China;
2. College of Information Engineering, Taiyuan University of Technology, Taiyuan 030024, China;
3. Key Laboratory of Embedded System and Service Computing, Ministry of Education, Tongji University, Shanghai 201804, China;
4. Department of Computer Science and Technology, Tongji University, Shanghai 201804, China
Keywords:
concept lattice; rough set; incomplete formal context; equivalence class; maximal tolerance class; information granulation; data processing
CLC:
TP18
DOI:
10.11992/tis.201809021
Abstract:
To improve the data processing ability of the concept lattice model and eliminate the impact of incomplete information, in this paper, considering the limitations of classical concept lattice in actual applications, the granulation idea in rough sets is integrated into concept lattice. First, we explore information granulation methods from the perspective of concept lattice and then propose a knowledge acquisition method based on the equivalence class and maximal tolerance class, and then, carry out the case analysis. These methods are helpful for the integration of concept lattice and rough sets. Moreover, they also provide some useful ideas for exploring the analysis and processing mechanism of incomplete formal contexts.
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