FCA4AI 2018
What can FCA do for Artificial Intelligence?

Table of Contents

• Preface
  
  

• Inductive Reasoning with Conceptual Space Representations (Invited Talk) 7-8
  Zied Bouraoui

• An Answer Set Programming Environment for High-Level Specification and Visualization of FCA 9-20
  Lucas Bourneuf
• Three Approaches for Mining Definitions from Relational Data in the Web of Data 21-32
  Justine Reynaud, Yannick Toussaint, Amedeo Napoli
• Relational Proportions Between Objects and Attributes 33-44
  Nelly Barbot, Laurent Miclet, Henri Prade
• MDL for FCA: Is There a Place for Background Knowledge? 45-56
  Tatiana Makhalova, Sergei O. Kuznetsov, Amedeo Napoli
• Rectangle and Square Coverings of Tolerance Spaces and Their Direct Product 57-68
  Christian Jäkel, Stefan E. Schmidt
• The Theory and Practice of Coupling Formal Concept Analysis to Relational Databases 69-80
  Jens Kötters, Peter W. Eklund
• Generalized Metrics with Applications to Ratings and Formal Concept Analysis 81-92
  Tobias Gäbel-Häkenschnieder, Thorsten Pfeiffer, Stefan E. Schmidt
• Binary Lattices 93-104
  Célia Châtel, François Brucker, Pascal Préa
• Biclustering Based on FCA and Partition Pattern Structures for Recommendation Systems 105-116
  Nyoman Juniarta, Victor Codocedo, Miguel Couceiro, Amedeo Napoli
• Combining Concept Annotation and Pattern Structures for Guiding Ontology Mapping 117-126
  Pierre Monnin, Amedeo Napoli, Adrien Coulet
• Understanding Collaborative Filtering with Galois Connections 127-143
  Vladimir Kursitys, Dmitry Ignatov