Semantic Web Dog Food

Presented at: 3rd European Semantic Web Conference (ESWC2006)

by Vít Nováček, Pavel Smrž

The significance of uncertainty representation has become obvious in the Semantic Web community recently. This paper presents our research on uncertainty handling in automatically created ontologies. A new framework for uncertain information processing is proposed. 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 discuss the universal internal format of uncertain conceptual structures in OLE then and offer a utilisation example then. The proposed format serves as a basis for empirical improvement of initial knowledge acquisition methods as well as for general explicit inference tasks.

Empiric Merging of Ontologies - A Proposal of Universal Uncertainty Representation Framework was presented at this event.

Keywords: Mapping / translation / matching / aligning (heterogeneity), Social networks and Semantic Web

Resource URI on the dog food server: http://data.semanticweb.org/conference/eswc/2006/paper/novacek-smrz
Same as: http://www.eswc2006.org/full-papers/#novacek-smrz

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