On the complexity of inferring functional dependencies
Discrete Applied Mathematics - Special issue on combinatorial problems in databases
Formal Concept Analysis: Mathematical Foundations
Formal Concept Analysis: Mathematical Foundations
A partition-based approach towards constructing Galois (concept) lattices
Discrete Mathematics
Computing iceberg concept lattices with TITANIC
Data & Knowledge Engineering
Building Concept (Galois) Lattices from Parts: Generalizing the Incremental Methods
ICCS '01 Proceedings of the 9th International Conference on Conceptual Structures: Broadening the Base
Concise Representation of Frequent Patterns Based on Generalized Disjunction-Free Generators
PAKDD '02 Proceedings of the 6th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
Theory of Relational Databases
Theory of Relational Databases
A parallel algorithm for lattice construction
ICFCA'05 Proceedings of the Third international conference on Formal Concept Analysis
On the complexity of computing generators of closed sets
ICFCA'08 Proceedings of the 6th international conference on Formal concept analysis
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Minimal generators (mingens) of concept intents are valuable elements of the Formal Concept Analysis (FCA) landscape, which are widely used in the database field, for data mining but also for database design purposes. The volatility of many real-world datasets has motivated the study of the evolution in the concept set under various modifications of the initial context. We believe this should be extended to the evolution of mingens. In the present paper, we build up on previous work about the incremental maintenance of the mingen family of a context to investigate the case of lattice merge upon context subposition. We first recall the theory underlying the singleton increment and show how it generalizes to lattice merge. Then we present the design of an effective merge procedure for concepts and mingens together with some preliminary experimental results about its performance.