Appel: Ontology Learning (ECAI)
Philippe Blache
pb at lpl.univ-aix.fr
Mon Mar 13 09:08:08 UTC 2000
From: Alexander Maedche <ama at aifb.uni-karlsruhe.de>
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*********** Call for Papers: Ontology Learning ******************
******************** ECAI-2000 Workshop **************************
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******************** August 22, 2000 **************************
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Comprehensive information to be found at
http://ol2000.aifb.uni-karlsruhe.de
Workshop Summary
Ontologies serve as a means for establishing a conceptually concise
basis for communicating knowledge for many purposes. In recent years,
we have seen a surge of interest that deals with the discovery and
automatic creation of complex, multirelational knowledge structures.
For example, the natural language community tries to acquire word
semantics from natural language texts, database researchers tackle
the problem of schema induction and integration, and people building
intelligent information agents research the learning of complex
structures from semi-structured input (HTML, XML). All the while,
efforts in the machine learning community pursue the induction of
more concise and more expressive knowledge structures
(e.g., relational learning) in general.
For the workshop we intend to gather a diverse range of participants
interested in the learning of ontologies. In particular, we are
also interested in the maintenance (revision, incrementality) and
integration (from various sources) aspects of learning ontologies.
We want to further, or even establish, the exchange of ideas between
these communities --- and maybe even others that we have not thought
of. Hence, we solicit papers that present innovative approaches to
ontology learning that are to be discussed in the workshop, system
demonstrations and applications or position statements.
Important Dates
Deadline for paper submission 1 April 2000
Notification of acceptance 1 May 2000
Deadline final contributions 1 June 2000
All accepted papers will be published in the workshop proceedings.
In addition, a few selected best papers will be considered for
publication in a special issue about Ontology Learning of Elsevier's
Journal "Data and Knowledge Engineering".
Submission Information
We invite contributions that advance the state-of-the-art in topics
related to the purpose of the workshop. Persons interested in
participating should submit either a technical paper (less than
5000 words) or a position paper (less than 1500 words) addressing
new research issues. In addition, we solicit proposals for panel
discussions and break-out groups that work towards visions for
ontology learning. Submit before April 1, 2000 in electronic form
(strongly preferred!) in postscript or pdf in the final
ECAI style format (cf. http://www.ecai2000.hu-berlin.de/style.html)
to:
ama at aifb.uni-karlsruhe.de
or send three hard copies of your submission to:
"Ontology Learning"
Steffen Staab and Alexander Maedche
Institute AIFB,
Karlsruhe University,
D-76128 Karlsruhe,
Germany
Organizing Committee
Steffen Staab (Contact),
AIFB, Karlsruhe University,
76128 Karlsruhe, Germany
email: sst at aifb.uni-karlsruhe.de
phone: +49-721-608 4751
fax: +49-721-693 717
Alexander Maedche, AIFB, Karlsruhe University
Claire Nedellec, Inference and Machine Learning Group,
LRI, Université Paris Sud
Peter Wiemer-Hastings, Division of Informatics,
University of Edinburgh
Program Committee
Illarramendi Echave Arantxa, Universidad del Pais Vasco, Spain
Dieter Fensel, Free University of Amsterdam, Amsterdam, NL
Nicola Guarino, National Research Council, Padova, Italy
Asuncion Gomez-Perez, Universidad Politecnica de Madrid, Spain
Udo Hahn, CLIF, University of Freiburg, Germany
Ian Horrocks, University of Manchester, UK
Paul Johannson, University of Stockholm, Sweden
Jörg-Uwe Kietz, Swiss Life, Zurich, Switzerland
Yves Kodratoff, LRI, France
Robert Meersman, Vrije Universiteit Brussel, Belgium
Christine Parent, University of Lausanne, Switzerland
Marie-Christine Rousset, LRI, France
Rudi Studer, Institute AIFB, University of Karlsruhe, Germany
Stefan Wrobel, University of Magdeburg, Germany
___________________________________________________________________
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