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(See workshop website)
Still, making full use of the knowledge contained on the Web is an ongoing challenge due to the special properties of the Web as an information source:
- Heterogeneity: web data occurs in any kind of formats, languages, data structures and terminology one can imagine.
- Decentrality: the Web is inherently decentralized which means that there is no central point of control that can ensure consistency or synchronicity.
- Scale: the Web is huge and processing data at web scale is a major challenge in particular for knowledge-intensive methods.
These characteristics make the Web a challenging but also a promising chance for AI methods that can help to make the knowledge on the Web more accessible for humans and machines by capturing, representing and using information semantics. The relevance and importance of AI methods for the Web is underlined by the fact that the AAAI – as one of the major AI conferences – has been featuring a special track “AI on the Web” for more than five years now. In line with this track and in order to stress this relevance within the German AI community, we are looking for work on relevant methods and their application to web data. Examples of such methods include but are not limited to:
- Logics and Reasoning
- Distributed Problem Solving
- Information Extraction
- Text Mining
- Machine Learning
- Probabilistic methods
- Argumentation
Examples of applications include but are not limited to:
Semantic Search
Data Integration
Ontologies
Knowledge Discovery
User Interfaces
Image Processing
Social Networks
It has become quite clear that in most cases a single method is insufficient for solving real-world problems. Therefore, we are particularly interested in approaches that combine insights from different areas of AI to solve problems on the web. Examples for such approaches include but are not limited to:
- Distributed Logical Reasoning
- Statistical Relational Learning
- Ontology-Based Natural Language Processing
- Uncertain Reasoning with Description Logics
The workshop welcomes full technical contributions containing an application of the described methods to real data on the web as the workshop is meant as a forum for discussing experiences with applying AI methods to real world data. Furthermore, interesting problems and position statements on issues involving the application of AI methods on the web can be submitted in form of short papers.
Important Dates:
Workshop: September 24, 2012
Workshop Organizers:
Sebastian Rudolph, Karlsruhe Intitute of Technology, Germany
Heiner Stuckenschmidt, University of Mannheim, Germany
Matthias Thimm, University of Koblenz-Landau, Germany
Program Committee:
Chris Biemann (Technische Universität Darmstadt, Germany)
Claudia D’Amato (Università degli Studi di Bari, Italy)
Gerd Gröner (Universität Koblenz-Landau, Germany)
Barbara Hammer (Universität Bielefeld, Germany)
Andreas Hotho (Universität Würzburg, Germany)
Yevgeny Kazakov (Universität Ulm, Germany)
Pavel Klinov (Universität Ulm, Germany)
Kristian Kersting (Universität Bonn, Germany)
Mathias Niepert (Universität Mannheim, Germany)
Rafael Peñaloza Nyssen (Technische Universität Dresden, Germany)
Ansgar Scherp (Universität Koblenz-Landau, Germany)
Michael Strube (Heidelberg Institute for Theoretical Studies, Germany)
Ingo J. Timm (Universität Trier, Germany)
Stefan Woltran (Technische Universität Wien, Austria)
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