Welcome

This website gives an overview of some ongoing research activities at AIFB. If you have any comments or questions please contact us.

Designing and refining ontologies becomes a tedious task, once the boundary to real-world-size knowledge bases has been crossed. Hence semi-automatic methods supporting those tasks will determine the future success of ontologies in practice. Our research therefore aims at the conceptual development and implementation of tools for semi-automatic ontology engineering. By combining Ontology Learning and Relational Exploration we hope to overcome the knowledge acquisition bottleneck, especially with respect to expressive axiomatizations (see our original paper at ICCS'2007). The RELExO framework supporting the refinement and evaluation of OWL DL ontologies is open source and publicly available under the LGPL license.

Ontology Learning

Ontology learning is a relatively new field of research which aims to support the tedious task of knowledge acquisition by automated techniques. It is supported by a variety of tools and frameworks including, e.g., LExO, LeDA or Text2Onto.


Relational Exploration

Facing the growing amount of information in today's society, the task of specifying human knowledge in a way that can be unambiguously processed by computers becomes more and more important. Two acknowledged fields in this evolving scientific area of Knowledge Representation are Description Logics (DL) and Formal Concept Analysis (FCA). While DL concentrates on characterizing domains via logical statements and inferring knowledge from these characterizations, FCA builds conceptual hierarchies on the basis of present data. Relational Exploration is a method for acquiring complete relational knowledge about a domain of interest by successively consulting a domain expert without ever asking redundant questions. This is achieved by combining DL and FCA: DL formalisms are used for defining FCA attributes while FCA exploration techniques are deployed to obtain or refine DL knowledge specifications.