[DL] 2nd CfP "Special Issue on Induction on the Semantic Web" for International Journal on Semantic Web and Information Systems (IJSWIS)

[Claudia d'Amato]

[Apologies for possible multiple copies]


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Call for Papers

International Journal on Semantic Web and Information Systems (IJSWIS)

Special Issue on "Induction on the Semantic Web"
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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 limitations to scale to large amounts of data. 
Alternative approaches such as data mining and machine learning methods have been found effective to 
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 kinds of approaches for 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 perspective 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 of Interest
The topics of interest of the special issue include, but are not limited to:

     * Knowledge Discovery and Ontologies:
           o data mining techniques using ontologies,
           o ontology mining and knowledge discovery from ontological knowledge bases,
           o ontology-based interpretation and validation of discovered knowledge,
           o whole knowledge discovery process guided by ontologies
     * Knowledge Discovery and Linked Data
           o learning ontologies from Linked Data
           o discovering hidden knowledge from Linked Data
           o learnig semantic relationship from Linked Data
     * Inductive Reasoning with Concept Languages:
           o inductive aggregation,
           o concept retrieval and query answering,
           o approximate classification,
           o inductive methods and fuzzy reasoning for ontology mapping,
           o construction, refinement and evolution of ontologies
           o concept change and novelty detection for ontology evolution
     * Statistical learning for the Semantic Web:
           o refinement operators for concept and rule languages,
           o concept and rules learning,
           o kernels and instance-based learning for structured representations,
           o semantic (dis-)similarity measures and conceptual clustering,
           o probabilistic methods for concept and rule languages
     * Other topics:
           o Open World Assumption (OWA) vs. Closed World Assumption (CWA) in learning,
           o applicability of relational learning in the Semantic Web context,
           o integration of induction and deduction,
           o evaluation methodologies and metrics for machine learning methods applied to ontologies
     * Applications:
           o challenges in practical applications of Machine Learning/Data Mining on the Semantic Web
           o life sciences,
           o cultural heritage,
           o semantic multimedia,
           o geo-informatics,
           o bio-informatics
           o Semantic Web Services
           o 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.



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.

Dates

     * October 1, 2010 -  Submission Deadline
     * January 1, 2011 -  Notifications
     * February 15, 2011 - Revised Papers
     * March 15, 2011 - Final Versions
     * Fall 2011 - Publication in a fall issue

Guest Editors

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