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SMRŽ, P. NOVÁČEK, V.
Original Title
Empirical Merging of Ontologies A Proposal of Universal Uncertainty Representation Framework
Type
conference paper
Language
English
Original Abstract
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.
Keywords
ontology, uncertainty
Authors
SMRŽ, P.; NOVÁČEK, V.
RIV year
2006
Released
11. 7. 2006
Publisher
Springer Verlag
Location
Berlin
ISBN
3-540-34544-2
Book
The Semantic Web: Research and Applications
Edition
Lecture notes in Computer Science 4011/2006 - Proceedings of ESWC'06 - the 3rd European Semantic Web Conference
Pages from
65
Pages to
79
Pages count
15
BibTex
@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" }