Fachbereich Elektrotechnik / Informatik
Wilhelmshöher Allee 73
tel +49 (0) 561 804 - 6266
fax +49 (0) 561 804 - 6259
I studied Computer Science with minor Psychology at the University of Freiburg. In May 2007, I joined the Knowledge and Data Engineering team in Kassel. I'm a senior developer of BibSonomy, and my scientific interests lie in the field of bridging the gap between the Social and the Semantic Web. In my dissertation, I analyzed methods to capture emergent semantics from social annotation systems.
Among others, my research in collaboration with several great colleagues has provided insight in the following areas:
Here you find a summary of my scientific activities related to conferences, workshops and journals.
This publication list is generated automatically from BibSonomy.
Most courses I have been teaching or assisisting were held in German.
My research is focussed around supporting users during knowledge interaction tasks like retrieval, structuring and collaboration. I am especially interested in Data Mining methods to discover latent Semantic information, e.g. in Social annotation data (e.g. from Tagging Systems). I see Ontology Learning approaches as a viable tools to bridge the gap between the Social and the Semantic Web.
Title: Capturing Emergent Semantics from Social Annotation Systems
The ongoing growth of the World Wide Web, catalyzed by the increasing possibility of ubiquitous access via a variety of devices, continues to strengthen its role as our prevalent information and commmunication medium. The vision of supporting both humans and machines in knowledge-based activities led to the development of different systems which allow to structure Web resources by metadata annotations. Interestingly, two major approaches which gained a considerable amount of attention are addressing the problem from nearly opposite directions: On the one hand, the idea of the Semantic Web suggests to formalize the knowledge within a particular domain by means of a ``top-down'' approach of defining ontologies. On the other hand, Social Annotation systems as part of the so-called Web 2.0 movement implement a ``bottom-up'' style of categorization using arbitrary keywords.
Experience as well as research in the characteristics of both systems has shown that their strengths and weaknesses seem to be inverse: While Social Annotation suffers from problems like, e.g. ambiguity or lack or precision, ontologies were especially designed to eliminate those. On the contrary, the latter suffer from a knowledge acquisition bottleneck, which is successfully overcome by the large user populations of Social Annotation systems. Instead of being regarded as competing paradigms, the obvious potential synergies from a combination of both motivated approaches to "bridge the gap" between them. Those were fostered by the evidence of emergent semantics, i.e. the self-organized evolution of implicit conceptual structures, within Social Annotation data. While several techniques to exploit the emergent patterns were proposed, a systematic analysis -- especially regarding paradigms from the field of ontology learning -- is still largely missing. This also includes a deeper understanding of the circumstances which affect the evolution processes.
This work aims to address this gap by providing an in-depth study of methods and influencing factors to capture emergent semantics from Social Annotation Systems. We focus hereby on the acquisition of lexical semantics from the underlying networks of keywords, users and resources. Structured along different ontology learning tasks, we use a methodology of semantic grounding to characterize and evaluate the semantic relations captured by different methods. In all cases, our studies are based on datasets from several Social Annotation Systems.
Finally, we discuss a set of applications which operationalize our results for enhancing both Social Annotation and semantic systems. In summary, the contributions of this work highlight viable methods and crucial aspects for designing enhanced knowledge-based services of a Social Semantic Web.
During my PhD, I have been involved in the following research, industry and software projects:
I participate in several Social Platforms - here you can find my latest activities.
Around my professional activities, I'm engaged at a number of projects and events I find more than worth to be supported: