Motivations of Extensive Incorporation of Uncertainty in OLEOntologies
Vít Nováček · 2006
Abstract. Recently, the significance of uncertain information representation has become obvious in the Semantic Web community. This paper presents an ongoing research of uncertainty handling in automatically created ontologies. Proposal of a specific framework is provided. The research is related to OLE (Ontology LEarning), a project aimed at bottom-up generation and merging of domain specific ontologies. Formal systems that underlie the uncertainty representation are briefly introduced. We will discuss a universal internal format of uncertain conceptual structures in OLE then. The proposed format serves as a basis for inference tasks performed among an ontology. These topics are outlined as motivations of our future work. 1