BOOK-CHAPTER

Relational Data,Formal Concept Analysis, and Graded Attributes

Abstract

Formal concept analysis is a particular method of analysis of relational data. Also, formal concept analysis provides elaborate mathematical foundations for relational data. In the course of the last decade, several attempts appeared to extend formal concept analysis to data with graded (fuzzy) attributes. Among these attempts, an approach based on residuated implications plays an important role. This chapter presents an overview of foundations of formal concept analysis of data with graded attributes, with focus on the approach based on residuated implications and on its extensions and particular cases. Presented is an overview of both of the main parts of formal concept analysis, namely, concept lattices and attribute implications, and an overview of the underlying foundations and related methods. In addition to that, the chapter contains an overview of topics for future research.

Keywords:
Formal concept analysis Computer science Residuated lattice Formal methods Fuzzy logic Artificial intelligence Software engineering Algorithm

Metrics

2
Cited By
0.38
FWCI (Field Weighted Citation Impact)
65
Refs
0.55
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Rough Sets and Fuzzy Logic
Physical Sciences →  Computer Science →  Computational Theory and Mathematics
Multi-Criteria Decision Making
Social Sciences →  Decision Sciences →  Management Science and Operations Research
Advanced Algebra and Logic
Physical Sciences →  Computer Science →  Computational Theory and Mathematics

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