https://www.openresearch.org/mediawiki/index.php?title=WBBTMine_2008&feed=atom&action=historyWBBTMine 2008 - Revision history2024-03-29T11:08:41ZRevision history for this page on the wikiMediaWiki 1.31.1https://www.openresearch.org/mediawiki/index.php?title=WBBTMine_2008&diff=6830&oldid=prev127.0.0.1: Event created2008-10-14T21:19:17Z<p>Event created</p>
<p><b>New page</b></p><div>{{Event<br />
| Acronym = WBBTMine 2008<br />
| Title = Wikis, Blogs, Bookmarking Tools - Mining the Web 2.0<br />
| Type = Conference<br />
| Series = <br />
| Field = World wide web<br />
| Homepage = www.kde.cs.uni-kassel.de/ws/wbbtmine2008<br />
| Start date = Sep 15, 2008 <br />
| End date = Sep 15, 2008<br />
| City= Antwerp<br />
| State = <br />
| Country = Belgium<br />
| Abstract deadline = <br />
| Submission deadline = Jun 16, 2008<br />
| Notification = Jul 16, 2008<br />
| Camera ready = <br />
}}<br />
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<pre><br />
Wikis, Blogs, Bookmarking Tools - Mining the Web 2.0 (WBBTMine'08)<br />
http://www.kde.cs.uni-kassel.de/ws/wbbtmine2008/<br />
Workshop at ECML/PKDD 2008 - Antwerp, Belgium, 15 Sept. 2008<br />
<br />
Important dates<br />
===============<br />
* Paper submission deadline: June 16<br />
* Author Notification: July 16<br />
* Camera Ready Papers: August 14<br />
* Workshop: September 15<br />
<br />
Overview<br />
========<br />
Many Web 2.0 applications have rapidly emerged on the Web. This indicates a<br />
currently ongoing grass-root creation of knowledge spaces on the Web. The <br />
reason for the success of cooperative Web tools (wikis, blogs, etc.) and <br />
resource sharing (social bookmark systems, photo sharing systems, etc.) lies <br />
mainly in the fact that no specific skills are needed for publishing and <br />
editing. Web 2.0 applications are a very interesting application area for <br />
data mining. Unlike in traditional data mining scenarios, data does not <br />
emerge from a small number of (heterogeneous) data sources, but virtually <br />
from millions of different sources. As there is only minimal coordination, <br />
these sources can overlap or diverge in many ways. These fundamental <br />
features of heterogeneity and independence, known from collaborative <br />
filtering, are not limited to ratings and recommendations but extend to <br />
arbitrary complex data and data mining tasks. Steps into this new and<br />
exciting application area are the analysis of this new data, then the<br />
adaptation of well-known data mining and machine learning algorithm and <br />
finally the development of new algorithms.<br />
<br />
As research analyzing Wikis, Blogs and the structure underlying Social<br />
Bookmarks matures (and Web 2.0 workshops and conferences begin to <br />
proliferate), this workshop seeks contributions focused on state-of-the-art <br />
data mining algorithm and machine learning methods on Web 2.0 data.<br />
Papers describing new algorithms working on Web 2.0 data or work discussing <br />
aspects on the intersection of Web 2.0 and Knowledge Discovery are also <br />
highly welcome. In short, we want to accelerate the process of identifying <br />
the power of advanced data mining operating on Web 2.0 data, as well as the <br />
process of advancing data mining through lessons learned in analyzing these <br />
new data.<br />
<br />
Topics of interest<br />
==================<br />
include, but are not limited to:<br />
* network analysis of social resources sharing systems<br />
* analysis of wikis and blogs<br />
* analysis of social online communities<br />
* discovering social structures and communities<br />
* analysis of network dynamics<br />
* discovering misuse and fraud<br />
* Web 2.0 personalization<br />
* Web 2.0 technologies for recommender systems<br />
* information retrieval in the Web 2.0<br />
* community detection<br />
* emergent semantics<br />
* Web 2.0 based ontology learning<br />
* predicting trends and user behavior<br />
* semantic association identification by link analysis<br />
* Web 2.0 crawling<br />
* mining information from distributed and re-combined Web 2.0 sources <br />
/ mash-ups<br />
* mobile Web 2.0: social search; mobile communities; ?<br />
* usage interfaces for mining: parallelization of Web and mobile interfaces; <br />
mash-up interfaces<br />
* interactions between usage interfaces and data collection, mining, and presentation<br />
* privacy challenges in Web 2.0 and mobile Web 2.0 applications<br />
* applications of any of the above methods and technologies<br />
<br />
Workshop chairs<br />
===============<br />
* Bettina Berendt, K.U. Leuven, Belgium<br />
* Natalie Glance, Google, USA<br />
* Andreas Hotho, University of Kassel, Germany<br />
---) Please contact us at wbbtmine08@gmail.com<br />
<br />
Program committee (to be extended)<br />
==================================<br />
Sarabjot Singh Anand, University of Warwick, UK<br />
Mathias Bauer, mineway, Germany<br />
Janez Brank, Jozef Stefan Institute, Slovenia<br />
Michelangelo Ceci, University of Bari, Italy<br />
Ed H. Chi, PARC, USA<br />
Brian Davison, Lehigh University, USA<br />
Marco de Gemmis, University of Bari, Italy<br />
Marko Grobelnik, Jozef Stefan Institute, Slovenia<br />
Pasquale Lops, University of Bari, Italy<br />
Ernestina Menasalvas, Universidad Politecnica de Madrid, Spain<br />
Dunja Mladenic, Jozef Stefan Institute, Slovenia<br />
Ion Muslea, SRI International, USA<br />
Giovanni Semeraro, University of Bari, Italy<br />
Ian Soboroff, National Institute of Standards and Technology, USA<br />
Myra Spiliopoulou, Otto-von-Guericke-Universitaet Magdeburg, Germany<br />
Gerd Stumme, University of Kassel, Germany<br />
Maarten van Someren, Universiteit van Amsterdam, The Netherlands<br />
Michael Wurst, University of Dortmund, Germany<br />
</pre>This CfP was obtained from [http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=3097&amp;copyownerid=2 WikiCFP][[Category:Data mining]]</div>127.0.0.1