Dear colleague, apologies for cross-posting. ------------------------------------------- The Fourth IJCAI International Workshop on Graph Based Knowledge Representation and Reasoning, July 2015, Buenos Aires, Argentina. Organizing Committee: · Madalina Croitoru <http://www.lirmm.fr/~croitoru>, Univ Montpellier, France · Pierre Marquis <http://www.cril.univ-artois.fr/~marquis/Home,_sweet_home.html>, CRIL-CNRS, France · Sebastian Rudolph <http://sebastian-rudolph.de/doku.php?id=home>, TU Dresden, Germany · Gem Stapleton <https://sites.google.com/site/stapletongem/home>, Engineering and Mathematics Moulescoomb Brighton, UK Important dates: · Submission Deadline: April 26th, 2015 · GKR 2015 Workshop (1 day): *July 25th-31st, 2015* *Post proceedings of the workshop will be published in a special issue of the SPRINGER LNAI Series.* Different paradigms for knowledge representation and their subsequent manipulation by dedicated reasoning systems have been successfully studied in the past. Nevertheless, new challenges, problems and issues have appeared in the context of knowledge representation in AI that involve the logical manipulation of increasingly large information sets (see for example Semantic Web, the Open Linked Data initiative, Social Networks etc.) Therefore, research into KRR must move towards investigating structures for representation optimally manipulated to perform large scale reasoning, given very new and different constraints to those existing only few years ago. Included in this new generation of KRR systems are graph-based knowledge representation formalisms. Such graph-based techniques have been successfully deployed in different research areas as dedicated formalisms. The advantages of graph-based KRR techniques are three-fold: (1) graphs provide a natural paradigm for modeling domains with a very complex structure; (2) a graph-based knowledge representation allows for a very intuitive graphical explanation of the knowledge reasoning process and (3) a graph-based knowledge representation typically allows for structure-based optimization of the reasoning process. Graph-based knowledge representation and reasoning is thus a growing area of research, spanning across different domains, with more and more important contributions appearing over the last few years. It is the investigation of further developments of KRR graph techniques that we address within this workshop. The workshop welcomes contributions on graph-based representation, query and reasoning paradigms (e.g. Baysian Networks (BNs), Semantic Networks (SNs), RDF/S, SPARQL \& RIF, Conceptual Graphs (CGs), Formal Concept Analysis (FCA), Euler Diagrams, CP-Nets, GAI-Nets, etc.) from a theoretical and application viewpoint. The papers will be judged from two perspectives: technical and application. Technical results will include graph theory based results for novel structures for representation, extensions of existing structures for added expressivity, conciseness, optimisation algorithms for reasoning, reasoning explanation mechanisms etc. Papers reporting on application experience will be expected to demonstrate the benefits of the proposed solutions. Examples of such domains include Semantic Web, Grid Computing, BioInformatics, Multi Agent Systems, Recommender Systems etc. The workshop is expected to bring together people from different research communities that are actively pursuing this line of research. We hope that the presentation of different perspectives on employing graphs for knowledge representation and reasoning will be mutually enriching and will stimulate further research. -- Dr Jim Burton Senior Lecturer in Computing School of Computing, Engineering and Mathematics University of Brighton ___________________________________________________________ This email has been scanned by MessageLabs' Email Security System on behalf of the University of Brighton. For more information see http://www.brighton.ac.uk/is/spam/ ___________________________________________________________