Formal Concept Analysis

1. Front Matter

   Pages i-xiii

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2. Invited Papers

   1. Front Matter

      Pages 1-1

      PDF

   2. Elements About Exploratory, Knowledge-Based, Hybrid, and Explainable Knowledge Discovery

      • Miguel Couceiro, Amedeo Napoli

      Pages 3-16

   3. Too Much Information: Can AI Cope with Modern Knowledge Graphs?

      • Markus Krötzsch

      Pages 17-31

   4. Learning Implications from Data and from Queries

      • Sergei Obiedkov

      Pages 32-44

   5. Concepts in Application Context

      • Steffen Staab

      Pages 45-52

3. Theory

   1. Front Matter

      Pages 53-53

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   2. Direct and Binary Direct Bases for One-Set Updates of a Closure System

      • Kira Adaricheva, Taylor Ninesling

      Pages 55-72

   3. Reduction and Introducers in d-contexts

      • Alexandre Bazin, Giacomo Kahn

      Pages 73-88

   4. Dualization in Lattices Given by Implicational Bases

      • Oscar Defrain, Lhouari Nourine

      Pages 89-98

   5. “Properties of Finite Lattices” by S. Reeg and W. Weiß, Revisited

      • Bernhard Ganter

      Pages 99-109

   6. Joining Implications in Formal Contexts and Inductive Learning in a Horn Description Logic

      • Francesco Kriegel

      Pages 110-129

   7. Lattices of Orders

      • Christian Meschke

      Pages 130-151

4. Methods and Applications

   1. Front Matter

      Pages 153-153

      PDF

   2. On-demand Relational Concept Analysis

      • Alexandre Bazin, Jessie Carbonnel, Marianne Huchard, Giacomo Kahn, Priscilla Keip, Amirouche Ouzerdine

      Pages 155-172

   3. Mining Formal Concepts Using Implications Between Items

      • Aimene Belfodil, Adnene Belfodil, Mehdi Kaytoue

      Pages 173-190

   4. Effects of Input Data Formalisation in Relational Concept Analysis for a Data Model with a Ternary Relation

      • Priscilla Keip, Alain Gutierrez, Marianne Huchard, Florence Le Ber, Samira Sarter, Pierre Silvie et al.

      Pages 191-207

   5. Parallelization of the GreConD Algorithm for Boolean Matrix Factorization

      • Petr Krajča, Martin Trnecka

      Pages 208-222

   6. Simultaneous, Polynomial-Time Layout of Context Bigraph and Lattice Digraph

      • Tim Pattison, Aaron Ceglar

      Pages 223-240

   7. Using Redescriptions and Formal Concept Analysis for Mining Definitions in Linked Data

      • Justine Reynaud, Yannick Toussaint, Amedeo Napoli

      Pages 241-256

This book constitutes the proceedings of the 15th International Conference on Formal Concept Analysis, ICFCA 2019, held in Frankfurt am Main, Germany, in June 2019.

The 15 full papers and 5 short papers presented in this volume were carefully reviewed and selected from 36 submissions. The book also contains four invited contributions in full paper length.

The field of Formal Concept Analysis (FCA) originated in the 1980s in Darmstadt as a subfield of mathematical order theory, with prior developments in other research groups. Its original motivation was to consider complete lattices as lattices of concepts, drawing motivation from philosophy and mathematics alike. FCA has since then developed into a wide research area with applications much beyond its original motivation, for example in logic, data mining, learning, and psychology.

• artificial intelligence
• association rules
• blind source separation
• clustering and classification
• concept lattices
• data mining
• databases
• discrete mathematics
• factorization
• Formal Concept Analysis (FCA)
• formal contexts
• graph drawings
• information analysis
• information extraction
• knowledge representation and reasoning
• knowledge-based system
• matrix algebra
• ontologies
• semantics

• Babeș-Bolyai University, Cluj-Napoca, Romania

  Diana Cristea

• University of Strasbourg, ENGEES, Strasbourg, France

  Florence Le Ber

• Frankfurt University of Applied Sciences, Frankfurt, Germany

  Baris Sertkaya

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