The development of effective techniques for knowledge representation and reasoning (KRR) is a crucial aspect of successful
intelligent systems. Different representation paradigms, as well as their use in dedicated reasoning systems, have been extensively
studied in the past. Nevertheless, new challenges, problems, and issues have emerged in the context of knowledge representation in
Artificial Intelligence (AI), involving the logical manipulation of increasingly large information sets (see for example Semantic Web, BioInformatics and so
on). Improvements in storage capacity and performance of computing infrastructure have also affected the nature of KRR systems,
shifting their focus towards representational power and execution performance. Therefore, KRR research is faced with a challenge of
developing knowledge representation structures optimized for large scale reasoning. This new generation of KRR systems includes
graph-based knowledge representation formalisms such as Bayesian Networks (BNs), Semantic Networks (SNs), Conceptual Graphs (CGs),
Formal Concept Analysis (FCA), CP-nets, GAI-nets, Argumentation Frameworks all of which have been successfully used in a number of applications. The goal of
this workshop is to bring together the researchers involved in the development and application of graph-based knowledge
representation formalisms and reasoning techniques.
The GKR 2013 opens a special graph database demonstration and application track. Papers submitted to this track should report on theory, implementation results and applications of graph databases. Short demo papers are also welcome.
- Website online 5 Dec 13