[DL] 2nd CfP: SI on Bridging the Gap - Data Mining and Social Network Analysis, Semantic Web & Web2.0

Andreas Hotho hotho at cs.uni-kassel.de
Wed Aug 26 10:13:37 CEST 2009

Second Call for Papers

         Special Issue of the Journal of Web Semantics

          *****  Special Issue on "Bridging the Gap"  *****
              Data Mining and Social Network Analysis
              for integrating Semantic Web and Web 2.0

/* http://www.kde.cs.uni-kassel.de/events/jws_special_issue_2010 */

Abstract submission:      21 September 2009
Submission deadline:      1  October 2009
Reviews due:              1  December 2009
Notification:             15 December 2009
Final version submitted:  15 January 2010
Publication:              April 2010

Focus of the Special Issue

The last years have seen increasing collaboration of researchers
from the Semantic Web, Web 2.0, social network analysis and machine
learning communities. Applications that use these research results
are achieving economic success. Data now become available that allow
researchers to analyze the use, acceptance and evolution of their

Highly popular user-centered applications such as Blogs, social
tagging systems, and Wikis have come to be known as "Web 2.0". A
major reason for their immediate success is the high ease of use of
new Web 2.0 services. These sites do not only provide data but also
generate an abundance of weakly structured metadata. A good example
is tagging. Here, users add keywords from an uncontrolled
vocabulary, called tags, to a resource. Such metadata are easy to
produce, but lack any kind of formal grounding, as used in the
Semantic Web.

The Semantic Web can complement the bottom-up effort of the Web 2.0
community in a top-down manner. Its central point is a stronger
knowledge representation based on some kind of ontology with a fixed
vocabulary and typed relations. Such a structure is typically
something users have in mind when they provide their information in
Web 2.0 systems. However, for further use, this structure is hidden
in the data and needs to be extracted. Techniques to analyze network
structures or weak knowledge representations as can be found in the
Web 2.0 have a long tradition in different other disciplines, like
social network analysis, machine learning and data mining. These
kinds of automatic mechanisms are necessary to extract the hidden
information and to reveal the structure in a way that the end user
can benefit from it. Using established methods to represent
knowledge gained from unstructured data will also be beneficial for
the Web 2.0 in that it provides Web 2.0 users with enhanced Semantic
Web features to structure their data.

For this special issue, we invite contributions which show how
synergies between Semantic Web and Web 2.0 techniques can be
successfully used. Since both communities work on network-like data
structures, analysis methods from different fields of research could
form a link between those communities. Techniques can be - but are
not limited to - social network analysis, graph analysis, machine
learning and data mining methods.

Topics of interest
Topics of interest for this special issue include, but are not
limited to:

     * ontology learning from Web 2.0 data
     * instance extraction from Web 2.0 systems
     * analysis of Blogs
     * discovering social structures and communities
     * predicting trends and user behaviour
     * analysis of dynamic networks
     * using content of the Web for modelling
     * discovering misuse and fraud
     * network analysis of social resource sharing systems
     * analysis of folksonomies and other Web 2.0 data structures
     * analysis of Web 2.0 applications and their data
     * deriving profiles from usage
     * personalized delivery of news and journals
     * Semantic Web personalization
     * Semantic Web technologies for recommender systems
     * ubiquitous data mining in Web (2.0) environment
     * applications

In accordance with the focus of the journal, the relatedness of your
submission to the Semantic Web will be an important evaluation

Submission Details

Submissions should describe original contributions and should not
have been published or submitted elsewhere. Submissions based on
conference papers should be extended and include a reference to the
corresponding proceedings. All submissions will be reviewed by at
least two reviewers. Final decisions on accepted papers will be
approved by an editor in chief.

Manuscripts should be prepared for publication in accordance with
instructions given in the "Guide for Authors":


The submission and review process will be carried out using
Elsevier's Web-based EES system, cf.

Guest Editors
  * Bettina Berendt, Katholieke Universiteit Leuven,
    Bettina.Berendt at cs.kuleuven.be
  * Andreas Hotho, University of Würzburg,
    hotho at informatik.uni-wuerzburg.de
  * Gerd Stumme, University of Kassel,
    stumme at cs.uni-kassel.de

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