Many Web 2.0 applications have rapidly emerged on the Web. This indicates a currently ongoing grass-root creation of knowledge spaces on the Web. The reason for the success of the upcoming tools for Web cooperation (wikis, blogs, etc.) and resource sharing (social bookmark systems, photo sharing systems, etc.) lies mainly in the fact that no specific skills are needed for publishing and editing. Web 2.0 applications are a very interesting application area for data mining. Unlike in traditional data mining scenarios, data does not emerge from a small number of (heterogeneous) data sources, but virtually from millions of different sources. As there is only minimal coordination, these sources can overlap or diverge in any possible way. This fundamental structure, known from collaborative filtering, is not limited to ratings and recommendations but can be applied to arbitrary complex data and data mining tasks. Steps into this new and exciting application area are the analysis of this new data, then the adaptation of well know data mining and machine learning algorithm and finally the development of new algorithms.
As research analyzing Wikis, Blogs and the structure underlying Social Bookmarks is beginning to mature (as shown in various Web 2.0, Wiki and Blogs workshops and conferences), this workshop seeks for contributions that make the next step and apply state-of-the-art data mining algorithm and machine learning methods on Web 2.0 data. Papers describing new algorithms working on Web 2.0 data or work discussing aspects on the intersection of Web 2.0 and Knowledge Discovery are also highly welcome. In short, we want to accelerate the process of identifying the power of advanced data mining operating on Web 2.0 data, as well as the process of advancing data mining through lessons learned in analyzing these new data.
The topics of the workshop include, but are not limited to:
We invite two types of submissions for this workshop:
Submitted papers will be peer-reviewed and selected on the basis of these reviews. Accepted papers will be presented at the workshop.
All submissions must be entered into the reviewing system Easychair in Postscript or PDF format. Although not required for the initial submission, we recommend to follow the format guidelines of ECML/PKDD (Springer LNCS -- LaTeX Style File), as this will be the required format for accepted papers.
The workshop proceedings will be distributed during the workshop. We plan to issue a post workshop publication of selected papers by Springer Lecture Notes.If you have further question please contact one of us or send a mail to: email@example.com