Empirical Merging of Ontologies A Proposal of Universal Uncertainty Representation Framework

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F06%3APU66903" target="_blank" >RIV/00216305:26230/06:PU66903 - isvavai.cz</a>
Alternative codes found
RIV/00216224:14330/06:00015341
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Empirical Merging of Ontologies A Proposal of Universal Uncertainty Representation Framework
Original language description
The significance of uncertainty representation has become<br>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<br>proposed format serves as a basis for empirical improvement of initial knowledge acquisition methods as well as for general explicit inference tasks.
Czech name
Empirical Merging of Ontologies A Proposal of Universal Uncertainty Representation Framework
Czech description
Příspěvek se zabývá zpracováním neurčitosti při automatickém vytváření ontologií.<br>

Project
<a href="/en/project/1ET100300419" target="_blank" >1ET100300419: Intelligent Models, Algorithms, Methods and Tools for the Semantic Web (realization)</a><br>
Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year
2006
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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