FCA4AI 2014
What can FCA do for Artificial Intelligence?

Table of Contents

• Preface
  
  

• Abstraction, Taxonomies, Connectivity: From AI to FCA and Back (invited talk) 7-8
  Henry Soldano
• Using Formal Concept Analysis to Create Pathways through Museum Collections 9-16
  Tim Wray, Peter Eklund
• Can FCA-based Recommender System Suggest a Proper Classifier? 17-26
  Yury Kashnitsky, Dmitry Ignatov
• Bicluster enumeration using Formal Concept Analysis 27-34
  Victor Codocedo, Amedeo Napoli
• Towards an FCA-based Recommender System for Black-Box Optimization 35-42
  Josefine Asmus, Daniel Borchmann, Ivo F. Sbalzarini, Dirk Walther
• Metric Generalization and Modification of Classification Algorithms Based on Formal Concept Analysis 43-50
  Evgeny Kolmakov
• Concept Stability as a Tool for Pattern Selection 51-58
  Aleksey Buzmakov, Sergei O. Kuznetsov, Amedeo Napoli
• About Universality and Flexibility of FCA-based Software Tools 59-65
  A.A. Neznanov, A.A. Parinov
• PRCA -- A Parallel Relational Concept Analysis Framework 66-76
  Ines Moosdorf, Adrian Paschke, Alexandru Todor, Jens Dietrich, Hans W. Guesgen
• Concept Building with Non-Hierarchical Relations Extracted from Text -- Comparing a Purely Syntactical Approach to a Semantic one 77-84
  Silvia Moraes, Vera Lima, Luis Furquim
• What can FCA do for Database Linkkey Extraction? 85-92
  Manuel Atencia, Jérôme David, Jérôme Euzenat
• Lattice-Based View Access: A way to Create Views over SPARQL Query for Knowledge Discovery 93-100
  Mehwish Alam, Amedeo Napoli