ENGLISH

Conceptual Structures: From Information to Intelligence: 18th International Conference on Conceptual Structures, ICCS 2010, Kuching, Sarawak, Malaysia, July 26-30, 2010. Proceedings

Book information

Publisher
Springer-Verlag Berlin Heidelberg
Year
2010
ISBN
9783642141973, 3642141978
DOI
10.1007/978-3-642-14197-3
Language
english
Format
PDF
Filesize
4 MB (4307675 bytes)
Series
Lecture Notes in Computer Science 6208 : Lecture Notes in Artificial Intelligence
Edition
1
Pages
207\218
Time added
2013-04-24 17:00:00

Description

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.

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