Extracting attribute implications from a formal context: unifying the basic approaches
From MaRDI portal
Publication:6658951
DOI10.1016/j.ins.2024.121419MaRDI QIDQ6658951
Jesús Medina, Didier Dubois, Henri Prade
Publication date: 8 January 2025
Published in: (Search for Journal in Brave)
Could not fetch data.
Cites Work
- Title not available (Why is that?)
- Title not available (Why is that?)
- Title not available (Why is that?)
- Title not available (Why is that?)
- Title not available (Why is that?)
- Title not available (Why is that?)
- Title not available (Why is that?)
- Title not available (Why is that?)
- Title not available (Why is that?)
- Title not available (Why is that?)
- Leibniz's logic and the ``cube of opposition
- Relating attribute reduction in formal, object-oriented and property-oriented concept lattices
- The multiple facets of the canonical direct unit implicational basis
- Formal concept analysis via multi-adjoint concept lattices
- Generating a condensed representation for association rules
- Direct-optimal basis computation by means of the fusion of simplification rules
- Rough-set-driven approach for attribute reduction in fuzzy formal concept analysis
- A fast compound algorithm for mining generators, closed itemsets, and computing links between equivalence classes
- Concept lattices with negative information: a characterization theorem
- Canonical dichotomous direct bases
- On heterogeneous formal contexts
- A multiview approach for intelligent data analysis based on data operators
- Using concept lattice theory to obtain the set of solutions of multi-adjoint relation equations
- Computing the Duquenne–Guigues basis: an algorithm for choosing the order
- Data mining algorithms to compute mixed concepts with negative attributes: an application to breast cancer data analysis
- Two Basic Algorithms in Concept Analysis
- Functional Dependencies in a Relational Database and Propositional Logic
- Fuzzy Galois Connections
- Data Mining and Machine Learning
- Actionability and Formal Concepts: A Data Mining Perspective
- A Formal Concept Analysis Approach to Rough Data Tables
- Theory and Applications of Relational Structures as Knowledge Instruments
- Connecting concept lattices with bonds induced by external information
- Disjunctive attribute dependencies in formal concept analysis under the epistemic view of formal contexts
- Preferences in discrete multi-adjoint formal concept analysis
- Formal concept analysis approach to understand digital evidence relationships
- Simplification logic for the management of unknown information
- Selection of appropriate bonds between \(\mathcal{L}\)-fuzzy formal contexts for recommendation tasks
This page was built for publication: Extracting attribute implications from a formal context: unifying the basic approaches
Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q6658951)