C4.5: programs for machine learning
C4.5: programs for machine learning
Formal Concept Analysis: Mathematical Foundations
Formal Concept Analysis: Mathematical Foundations
ICCS '99 Proceedings of the 7th International Conference on Conceptual Structures: Standards and Practices
RSKD '93 Proceedings of the International Workshop on Rough Sets and Knowledge Discovery: Rough Sets, Fuzzy Sets and Knowledge Discovery
Theory of Relational Databases
Theory of Relational Databases
Adding background knowledge to formal concept analysis via attribute dependency formulas
Proceedings of the 2008 ACM symposium on Applied computing
Relations of attribute reduction between object and property oriented concept lattices
Knowledge-Based Systems
Navigation in Knowledge-Based System for Helpdesk Based on FCA
ICCS '07 Proceedings of the 15th international conference on Conceptual Structures: Knowledge Architectures for Smart Applications
MDAI '07 Proceedings of the 4th international conference on Modeling Decisions for Artificial Intelligence
Extending Attribute Dependencies for Lattice-Based Querying and Navigation
ICCS '08 Proceedings of the 16th international conference on Conceptual Structures: Knowledge Visualization and Reasoning
ISMIS '09 Proceedings of the 18th International Symposium on Foundations of Intelligent Systems
Analyzing Social Networks Using FCA: Complexity Aspects
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
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
Towards concise representation for taxonomies of epistemic communities
CLA'06 Proceedings of the 4th international conference on Concept lattices and their applications
Attribute reduction in fuzzy concept lattices based on the T implication
Knowledge-Based Systems
Selecting important concepts using weights
ICFCA'11 Proceedings of the 9th international conference on Formal concept analysis
Data weeding techniques applied to Roget's thesaurus
KONT'07/KPP'07 Proceedings of the First international conference on Knowledge processing and data analysis
Formal concept analysis with constraints by closure operators
ICCS'06 Proceedings of the 14th international conference on Conceptual Structures: inspiration and Application
Basic level of concepts in formal concept analysis
ICFCA'12 Proceedings of the 10th international conference on Formal Concept Analysis
Exploring Users' Preferences in a Fuzzy Setting
Electronic Notes in Theoretical Computer Science (ENTCS)
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An important topic in formal concept analysis is to cope with a possibly large number of formal concepts extracted from formal context (input data). We propose a method to reduce the number of extracted formal concepts by means of constraints expressed by particular formulas (attribute-dependency formulas, ADF). ADF represent a form of dependencies specified by a user expressing relative importance of attributes. ADF are considered as additional input accompanying the formal context 〈X, Y, I〉. The reduction consists in considering formal concepts which are compatible with a given set of ADF and leaving out noncompatible concepts. We present basic properties related to ADF, an algorithm for generating the reduced set of formal concepts, and demonstrating examples.