Empirical Merging of Ontologies A Proposal of Universal Uncertainty Representation Framework
| Autoři | |
|---|---|
| Rok publikování | 2006 |
| Druh | Článek ve sborníku |
| Konference | The Semantic Web: Research and Applications (Lecture notes in Computer Science 4011 / 2006 - Proceedings of ESWC'06 - 3rd European Semantic Web Conference) |
| Fakulta / Pracoviště MU | |
| Citace | |
| www | http://nlp.fi.muni.cz/projects/ole/pubs.html |
| Obor | Informatika |
| Klíčová slova | knowledge acquisition; ontology; uncertainty representation |
| Popis | 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. |
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