CFP IRMLeS'09: deadline extension

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CALL FOR PAPERS

IRMLeS'09
1st Int. Workshop on Inductive Reasoning and Machine Learning on the
Semantic Web
http://irmles2009.di.uniba.it

To be held as part of the 6th European Semantic Web Conference (ESWC) in
June of 2009 in Heraklion, Crete (Greece).

Open, distributed and inherently incomplete nature of the Semantic Web
environment posses problems for deductive approaches, traditionally 
employed
to reason with logic-based ontological data. Hence, one may witness a 
recent
trend in the Semantic Web community to propose complementary forms of
reasoning, preferably more efficient and noise-tolerant. Promising and
already successful approach is the use of inductive and statistical methods
as complement to deductive one (for example by adding data mining 
support to
SPARQL query evaluation). It is especially valid when data comes from
distributed sources and may be inconsistent.
The IRMLeS workshop puts special attention on the problem of ontology
mining and inductive and statistical approximate reasoning.
The focus of the workshop is on discussion how machine learning techniques,
such as statistical learning methods and inductive forms of reasoning, can
work directly on the richly structured Semantic Web data and exploit the
Semantic Web technologies, and what is the added value of machine learning
methods in the Semantic Web context.
The workshop is meant to be a forum for scientific exchange amongst
researchers interested in an interdisciplinary research on the intersection
of the Semantic Web with Knowledge Discovery and Machine Learning fields.



AUDIENCE

The intended audience for this workshop includes:
. Semantic Web researchers interested in methods for intelligent data
analysis and inductive and statistical approximate reasoning
. Researchers in machine learning and data mining with interest in the
Semantic Web technologies
. Developers of applications of the Semantic Web technologies that contain
components realizing inductive and statistical approximate reasoning, data
mining and/or machine learning tasks
. Knowledge engineers and ontology developers interested in semi-automatic
methods for ontology mining, namely ontology construction and evolution


TOPICS

The topics of interest of the workshop include, but are not limited to:

. Knowledge Discovery and Ontologies
- Data mining techniques using ontologies
- Ontology Mining and Knowledge Discovery in ontological knowledge bases
- Ontology-based interpretation and validation of discovered knowledge
- Graph mining for ontologies
- Evaluation methodologies and metrics for the interaction of knowledge
discovery and ontologies

. Inductive Reasoning with Concept Languages
- inductive concept retrieval and query answering
- approximate classification
- inductive methods for ontology construction
- concept change and novelty detection for ontology evolution
- rule induction for ontology mapping
- fuzzy reasoning for ontology construction and evolution

. Statistical learning in the context of standard Semantic Web languages
- refinement operators for concept and rule languages
- concept learning and Web rules learning
- kernels and instance-based learning for structured representations
- semantic distances, dissimilarity measures and conceptual clustering
- extensions of Bayesian methods for concept and rule languages

. Knowledge-intensive learning from:
- Linked Open Data and Semantic Networks
- semi-structured data e.g. semantic mark-up mixed with text content (RSS,
RDFa, microformats, DublinCore)

. Applications (life sciences, cultural heritage, semantic multimedia,.) 
and
Tools

FORMAT

The workshop will include invited talk(s), presentations (technical,
application and position papers) and a wrap-up discussion.

SUBMISSIONS

Submissions (in PDF or PostScript format) should be written in English, and
not longer than 12 pages (full paper) or 5 pages (position paper), 
following
the ESWC formatting style (Springer LNCS).
All submissions will be reviewed by at least 2 reviewers.

In addition to the ESWC workshop proceedings, depending on the quality and
quantity of submissions, it is intended to publish a selection of revised
accepted papers in a journal special issue or a book volume.

ORGANIZING COMMITTEE

Claudia d'Amato, University of Bari, Italy
Nicola Fanizzi, University of Bari, Italy
Marko Grobelnik, Joz(ef Stefan Institute, Slovenia
Agnieszka Lawrynowicz, Poznan University of Technology, Poland
Vojtech Svatek, University of Economics, Prague, Czech Republic


PROGRAM COMMITTEE

Sarabjot S. Anand - University of Warwick
Bettina Berendt - Katholieke Universiteit Leuven
Sonia Bergamaschi - University of Modena-Reggio Emila
Sebastian Blohm - University of Karlsruhe
Floriana Esposito - University of Bari
Mohand-Said Hacid - Univ. Lyon 1
Pascal Hitzler - University of Karlsruhe
Andreas Hotho - University of Kassel
Jose Iria - University of Sheffield
Maciej Janik - University of Koblenz-Landau
Matthias Klush - DFKI - German Research Center for Artificial Intelligence
Jens Lehmann -- University of Leipzig
Francesca Alessandra Lisi - University of Bari
Thomas Lukasiewicz - Oxford University
Matthias Nickles - University of Bath
Sebastian Rudolph - University of Karlsruhe
Steffen Staab - University of Koblenz-Landau
Umberto Straccia - ISTI-CNR
York Sure - SAP
Valentina Tamma - University of Liverpool
Johanna Voelker - University of Karlsruhe

DATES

*Deadline: March 13, 2009 extended*
Notification: April 4, 2009
Camera ready: April 18, 2009
Workshop day: June 1st, 2009


FURTHER INFORMATION

http://irmles2009.di.uniba.it

-- 
Nicola Fanizzi
Dipartimento di Informatica . Università di Bari
Via E. Orabona, 4 . 70125 Bari . Italy
http://www.di.uniba.it/~fanizzi
tel: +39-80-5442246 . fax: +39-80-5443196
http://www.linkedin.com/in/nicolafanizzi