Efficient mining of association rules using closed itemset lattices
Information Systems
Formal Concept Analysis: Mathematical Foundations
Formal Concept Analysis: Mathematical Foundations
Computing iceberg concept lattices with TITANIC
Data & Knowledge Engineering
Automatic Structuring of Knowledge Bases by Conceptual Clustering
IEEE Transactions on Knowledge and Data Engineering
The semantic web: yet another hip?
Data & Knowledge Engineering - DKE 40
Monotone concepts for formal concept analysis
Discrete Applied Mathematics - Discrete mathematics & data mining (DM & DM)
Concept lattices and similarity in non-commutative fuzzy logic
Fundamenta Informaticae
Fuzzy inference based on fuzzy concept lattice
Fuzzy Sets and Systems
Information Sciences: an International Journal
Reduction method for concept lattices based on rough set theory and its application
Computers & Mathematics with Applications
Set approximations in fuzzy formal concept analysis
Fuzzy Sets and Systems
A multiview approach for intelligent data analysis based on data operators
Information Sciences: an International Journal
Concept analysis via rough set and AFS algebra
Information Sciences: an International Journal
Concept lattices of fuzzy contexts: Formal concept analysis vs. rough set theory
International Journal of Approximate Reasoning
Granular Computing and Knowledge Reduction in Formal Contexts
IEEE Transactions on Knowledge and Data Engineering
Axiomatic Fuzzy Set Theory and Its Applications
Axiomatic Fuzzy Set Theory and Its Applications
Optimal triangular decompositions of matrices with entries from residuated lattices
International Journal of Approximate Reasoning
Discovery of optimal factors in binary data via a novel method of matrix decomposition
Journal of Computer and System Sciences
Formal concept analysis with background knowledge: attribute priorities
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews - Special issue on information reuse and integration
Formal concept analysis in information science
Annual Review of Information Science and Technology
Short Communication: Concept lattice reduction using fuzzy K-Means clustering
Expert Systems with Applications: An International Journal
On multi-adjoint concept lattices: definition and representation theorem
ICFCA'07 Proceedings of the 5th international conference on Formal concept analysis
Ontology-based concept similarity in Formal Concept Analysis
Information Sciences: an International Journal
Approaches to knowledge reduction in generalized consistent decision formal context
Mathematical and Computer Modelling: An International Journal
Information Sciences: an International Journal
On lower and upper intension order relations by different cover concepts
Information Sciences: an International Journal
A generalization of near set model
RSKT'11 Proceedings of the 6th international conference on Rough sets and knowledge technology
Note on generating fuzzy concept lattices via Galois connections
Information Sciences: an International Journal
On multi-adjoint concept lattices based on heterogeneous conjunctors
Fuzzy Sets and Systems
Development of Near Sets Within the Framework of Axiomatic Fuzzy Sets
Fundamenta Informaticae
Formal concept analysis based on the topology for attributes of a formal context
Information Sciences: an International Journal
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Formal concept analysis (FCA) originally proposed by Wille [39], is an important theory for data analysis and knowledge discovery. Concept lattice is the core of the mathematical theory of formal concept analysis. To address the requirements of real word applications, concept lattice has been extended to many other forms from the theoretical point of view and possible applications. In this paper, with the aim of deriving the mathematical properties of formal concepts from the point of algebra, we propose a new algebra system for the formal context. Under the frame of the proposed system, some interesting properties of formal concepts are explored, which could be applied to explore concept hierarchy and ontology merging.