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From:
James Burton <[log in to unmask]>
Reply To:
James Burton <[log in to unmask]>
Date:
Wed, 18 Feb 2015 15:46:01 +0000
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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

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