Conceptual Structures: From Information to Intelligence

1. Front Matter

   PDF

2. Invited Papers

   1. Entities and Surrogates in Knowledge Representation

      • Michel Chein

      Pages 1-1

   2. Exploring Conceptual Possibilities

      • Bernhard Ganter

      Pages 2-2

   3. Graphical Representation of Ordinal Preferences: Languages and Applications

      • Jérôme Lang

      Pages 3-9

   4. Combining Description Logics, Description Graphs, and Rules

      • Boris Motik

      Pages 10-12

   5. Practical Graph Mining

      • Mohammed J. Zaki

      Pages 13-13

3. Accepted Papers

   1. Use of Domain Knowledge in the Automatic Extraction of Structured Representations from Patient-Related Texts

      • Galia Angelova

      Pages 14-27

   2. Translations between RDF(S) and Conceptual Graphs

      • Jean-François Baget, Madalina Croitoru, Alain Gutierrez, Michel Leclère, Marie-Laure Mugnier

      Pages 28-41

   3. Default Conceptual Graph Rules, Atomic Negation and Tic-Tac-Toe

      • Jean-François Baget, Jérôme Fortin

      Pages 42-55

   4. On the Stimulation of Patterns

      • Ryan Bissell-Siders, Bertrand Cuissart, Bruno Crémilleux

      Pages 56-69

   5. Ontology-Based Understanding of Natural Language Queries Using Nested Conceptual Graphs

      • Tru H. Cao, Anh H. Mai

      Pages 70-83

   6. An Easy Way of Expressing Conceptual Graph Queries from Keywords and Query Patterns

      • Catherine Comparot, Ollivier Haemmerlé, Nathalie Hernandez

      Pages 84-96

   7. Natural Intelligence – Commonsense Question Answering with Conceptual Graphs

      • Fatih Mehmet Güler, Aysenur Birturk

      Pages 97-107

   8. Learning to Map the Virtual Evolution of Knowledge

      • Mary Keeler

      Pages 108-124

   9. Branching Time as a Conceptual Structure

      • Peter Øhrstrøm, Henrik Schärfe, Thomas Ploug

      Pages 125-138

   10. Formal Concept Analysis in Knowledge Discovery: A Survey

       • Jonas Poelmans, Paul Elzinga, Stijn Viaene, Guido Dedene

       Pages 139-153

   11. Granular Reduction of Property-Oriented Concept Lattices

       • Ling Wei, Xiao-Hua Zhang, Jian-Jun Qi

       Pages 154-164

   12. Temporal Relational Semantic Systems

       • Karl Erich Wolff

       Pages 165-180

4. Accepted Posters

   1. FcaBedrock, a Formal Context Creator

      • Simon Andrews, Constantinos Orphanides

      Pages 181-184

   2. From Generalization of Syntactic Parse Trees to Conceptual Graphs

      • Boris A. Galitsky, Gábor Dobrocsi, Josep Lluis de la Rosa, Sergey O. Kuznetsov

      Pages 185-190

th The 18 International Conference on Conceptual Structures (ICCS 2010) was the latest in a series of annual conferences that have been held in Europe, A- tralia, and North America since 1993. The focus of the conference has been the representation and analysis of conceptual knowledge for research and practical application. ICCS brings together researchers and practitioners in information and computer sciences as well as social science to explore novel ways that c- ceptual structures can be deployed. Arising from the research on knowledge representation and reasoning with conceptual graphs, over the years ICCS has broadened its scope to include in- vations from a wider range of theories and related practices, among them other forms of graph-based reasoning systems like RDF or existential graphs, formal concept analysis, Semantic Web technologies, ontologies, concept mapping and more. Accordingly, ICCS represents a family of approaches related to conc- tualstructuresthatbuild onthesuccesseswithtechniquesderivedfromarti?cial intelligence, knowledge representation and reasoning, applied mathematics and lattice theory, computational linguistics, conceptual modeling and design, d- grammatic reasoning and logic, intelligent systems and knowledge management. The ICCS 2010 theme “From Information to Intelligence” hints at unve- ing the reasoning capabilities of conceptual structures. Indeed, improvements in storage capacity and performance of computing infrastructure have also - fected the nature of knowledge representation and reasoning (KRR) systems, shifting their focus toward representational power and execution performance. Therefore, KRR research is now faced with a challenge of developing knowledge representation and reasoning structures optimized for such reasonings.

• computational linguistics
• concept lattices
• graph mining
• intelligence
• knowledge discovery
• knowledge representation
• ontologies
• ontology
• semantic structures
• semantic web

• LIRMM, Université Montpellier,  

  Madalina Croitoru

• Irisa/Ifsic, Université de Rennes 1, Rennes cedex, France

  Sébastien Ferré

• MIMOS BERHAD, Kuala Lumpur, MALAYSIA

  Dickson Lukose

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