Foundations of logic programming
Foundations of logic programming
Information Processing Letters
Information Processing Letters
Building and maintaining analysis-level class hierarchies using Galois Lattices
OOPSLA '93 Proceedings of the eighth annual conference on Object-oriented programming systems, languages, and applications
Using Lattice-Based Framework as a Tool for Feature Extraction
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Efficiently Mining Maximal Frequent Itemsets
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Maintaining Class Membership Information
OOIS '02 Proceedings of the Workshops on Advances in Object-Oriented Information Systems
iO2 - An Algorithmic Method for Building Inheritance Graphs in Object Database Design
ER '96 Proceedings of the 15th International Conference on Conceptual Modeling
Discrete Applied Mathematics - Special issue: The 1998 conference on ordinal and symbolic data analysis (OSDA '98)
Theory of Relational Databases
Theory of Relational Databases
Topological space for attributes set of a formal context
RSKT'07 Proceedings of the 2nd international conference on Rough sets and knowledge technology
Fundamental study: The multiple facets of the canonical direct unit implicational basis
Theoretical Computer Science
Multi-agents and non-classical logic systems
IUKM'11 Proceedings of the 2011 international conference on Integrated uncertainty in knowledge modelling and decision making
On the recognition of k-equistable graphs
WG'12 Proceedings of the 38th international conference on Graph-Theoretic Concepts in Computer Science
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In the context of extracting maximal item sets and association rules from a binary data base, the graph-theoretic notion of domination was recently used to characterize the neighborhood of a concept in the corresponding lattice. In this paper, we show that the notion of domination can in fact be extended to any closure operator on a finite universe and be efficiently encoded into propositional Horn functions. This generalization enables us to endow notions and algorithms related to Formal Concept Analysis with Horn minimization and minimal covers of functional dependencies in Relational Databases.