Detail výsledku
Empirical Merging of Ontologies A Proposal of Universal Uncertainty Representation Framework
Nováček Vít
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 bottomup 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.
ontology, uncertainty
@inproceedings{BUT22212,
author="Pavel {Smrž} and Vít {Nováček}",
title="Empirical Merging of Ontologies A Proposal of Universal Uncertainty Representation Framework",
booktitle="The Semantic Web: Research and Applications",
year="2006",
series="Lecture notes in Computer Science 4011/2006 - Proceedings of ESWC'06 - the 3rd European Semantic Web Conference",
pages="65--79",
publisher="Springer Verlag",
address="Berlin",
isbn="3-540-34544-2"
}