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Intl. Journal on Semantic Web and Information Systems: Special Issue on Induction on the Semantic Web

From: Abraham Bernstein <bernstein@ifi.uzh.ch>
Date: Tue, 08 Jun 2010 18:05:14 +0200
Message-ID: <4C0E6A3A.5080504@ifi.uzh.ch>
To: semantic-web@w3.org
Special Issue on Induction on the Semantic Web

in the

International Journal on Semantic Web and Information Systems 
(http://www.ijswis.org/)
======================================================================================

Submission deadline: September 15, 2010


Overview
Increasingly, real-world data is published in the Semantic Web
languages. The vast availability of these data has uncovered one of the
main current limitations of deductive reasoning (generally adopted in
the Semantic Web context), i.e., its severe limitation when scaling to
large amounts of data. Alternative approaches such as data mining and
machine learning methods could effectively cope with the web's scale and
can also be used to capture new knowledge emerging from the data that is
not logically derivable.

However, exploiting this global resource of data requires new
perspective in perfoming data mining and machine learning that need to
be able to deal with the heterogeneity and complexity of Semantic Web
data. Depending on the data sources under consideration and the point of
view of the individual researcher, the idiosyncrasies of the Semantic
web -- e.g., the expressivity of the employed language, the richness of
the ontologies novel assumptions (e.g., "open world") -- might play a
major role in the analysis..

The primary goal of the special issue is to showcase cutting edge
research on the intersection of the Semantic Web with Knowledge
Discovery and Machine Learning, e.g.:

  - How can machine learning techniques, such as statistical learning
    methods and inductive forms of reasoning, work directly on the richly
    structured Semantic Web data and exploit the Semantic Web technologies?

  - How could machine learning techniques contribute to the full
    realization of the Semantic Web view?

  - What are the challenges for developers of machine learning techniques
    for the Semantic Web data?


Topics

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

- Knowledge Discovery and Ontologies:
   - data mining techniques using ontologies,
   - ontology mining and knowledge discovery from ontological knowledge 
bases,
   - ontology-based interpretation and validation of discovered knowledge,
   - whole knowledge discovery process guided by ontologies

- Knowledge Discovery and Linked Data:
   - learning ontologies from Linked Data,
   - discovering hidden knowledge from Linked Data,
   - learning semantic relationship from Linked Data

- Inductive Reasoning with Concept Languages:
   - inductive aggregation,
   - concept retrieval and query answering,
   - approximate classification,
   - inductive methods and fuzzy reasoning for ontology mapping,
   - construction, refinement and evolution of ontologies
   - concept change and novelty detection for ontology evolution

- Statistical learning for the Semantic Web:
   - refinement operators for concept and rule languages,
   - concept and rules learning,
   - kernels and instance-based learning for structured representations,
   - semantic (dis-)similarity measures and conceptual clustering,
   - probabilistic methods for concept and rule languages

- Other topics:
   - Open World Assumption (OWA) vs. Closed World Assumption (CWA) in 
learning,
   - applicability of relational learning in the Semantic Web context,
   - integration of induction and deduction,
   - evaluation methodologies and metrics for machine learning methods 
applied to ontologies

- Applications:
   - challenges in practical applications of Machine Learning/Data 
Mining on the Semantic Web
   - life sciences,
   - cultural heritage,
   - semantic multimedia,
   - geo-informatics,
   - bio-informatics,
   - Semantic Web Services,
   - and others

Submission Process

Submissions to this special issue should follow the journal's guidelines
for submission, and be made via the IJSWIS Submission System. After
submitting a paper, please also inform the guest editors by email.
Papers must be of high quality and should clearly state the technical
issue(s) being addressed as related to Induction on the Semantic Web.
Wherever possible, submissions should demonstrate the contribution of
the research by reporting on a systematic evaluation of the work. If a
submission is based on a prior publication in a workshop or conference,
the journal submission must involve substantial advance (a minimum of
30%) in conceptual terms as well as in exposition (e.g., more
comprehensive testing/evaluation/validation or additional
applications/usage). If this applies to your submission, please
explicitly reveal the relevant previous publications and describe
enhancements to the previous version as an appendix so the reviewers
have easy access to the details.

The recommended length of submitted papers is between 5,500 to 8,000
words. All papers are subject to peer review performed by at least three
established researchers drawn from a panel of experts selected for this
special issue. Accepted papers will undergo for a second cycle of
revision and reviewer feedback. Please submit manuscripts as a PDF file
using the online submission system.

The International Journal on Semantic Web and Information Systems
(IJSWIS) is the first Semantic Web journal to be included in the Thomson
ISI citation index. More information on the journal can be found at
http://www.ijswis.org.

Important Dates

- Submission Deadline: September 15, 2010
- Notifications: January 1, 2011
- Revised Papers (after Revisions): February 15, 2011
- Final Versions: March 15, 2011
- Publication in a 2011 issue: 2011
- Organizing Committee

Special Issue Guest Editors:

- Abraham Bernstein, University of Zurich, Switzerland,
- Claudia d'Amato, University of Bari, Italy,
- Volker Tresp, Siemens AG, Germany

-- 
-----------------------------------------------------------------
|  Professor Abraham Bernstein, PhD
|  University of Zürich, Department of Informatics
|  web: http://www.ifi.uzh.ch/ddis/bernstein.html
Received on Tuesday, 8 June 2010 16:05:47 GMT

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