FCA4AI 2012
What can FCA do for Artificial Intelligence?

Table of Contents

• Preface
  
  

• Relational Concept Analysis: A Synthesis and Open Questions (Invited Talk) 5
  Marianne Huchard
• Formal Concept Analysis Applied to Transcriptomic Data 7-14
  Mehwish Alam, Adrien Coulet, Amedeo Napoli, Malika Smaïl-Tabbone
• A New Approach to Classification by Means of Jumping Emerging Patterns 15-22
  Aleksey Buzmakov, Sergei O. Kuznetsov, Amedeo Napoli
• Semantic Querying of Data Guided by Formal Concept Analysis 23-32
  Victor Codocedo, Ioanna Lykourentzou, Amedeo Napoli
• Information Retrieval by On-line Navigation in the Latticial Space-search of a Database, with Limited Objects Access 33-40
  Christophe Demko, Karell Bertet
• Relational Data Exploration by Relational Concept Analysis 41-44
  Xavier Dolques, Marianne Huchard, Florence Le Ber, Clémentine Nebut
• Let the System Learn a Game: How Can FCA Optimize a Cognitive Memory Structure 45-52
  William Dyce, Thibaut Marmin, Namrata Patel, Clément Sipieter, Guillaume Tisserant, Violaine Prince
• An Approach to Semantic Content Based Image Retrieval Using Logical Concept Analysis 53-56
  Clément Guérin, Karell Bertet, Arnaud Revel
• Classification Reasoning as a Model of Human Commonsense Reasoning 57-64
  Xenia A. Naidenova
• Finding Errors in New Object in Formal Contexts 65-72
  Artem Revenko, Sergei O. Kuznetsov, Bernhard Ganter
• Finding Minimal Rare Itemsets in a Depth-first Manner 73-80
  Laszlo Szathmary, Petko Valtchev, Amedeo Napoli, Robert Godin
• A System for Knowledge Discovery in Big Dynamical Text Collections 81-87
  Sergei O. Kuznetsov, Alexey A. Neznanov, Jonas Poelmans