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@inproceedings{713796,
author = {Nováček, Vít},
address = {Portugal},
booktitle = {Proceedings of ICEIS 2007, vol. Artificial Intelligence and Decision Support Systems},
keywords = {ontology engineering; ontology learning; taxonomy acquisiton; uncertainty},
language = {eng},
location = {Portugal},
isbn = {978-972-8865-89-4},
note = {In press.},
pages = {31-38},
publisher = {INSTICC},
title = {Imprecise Empirical Ontology Refinement: Application to Taxonomy Acquisition},
year = {2007}
}
TY - JOUR
ID - 713796
AU - Nováček, Vít
PY - 2007
TI - Imprecise Empirical Ontology Refinement: Application to Taxonomy Acquisition
PB - INSTICC
CY - Portugal
SN - 9789728865894
N1 - In press.
KW - ontology engineering
KW - ontology learning
KW - taxonomy acquisiton
KW - uncertainty
N2 - The significance of uncertainty representation has become obvious in the Semantic Web community recently. This paper presents new results of our research on uncertainty incorporation into ontologies created automatically by means of Human Language Technologies. The research is related to OLE (Ontology LEarning)\footnote{The project's web page can be found at URL: \url{http://nlp.fi.muni.cz/projects/ole/}.} -- a project aimed at bottom-up generation and merging of ontologies. It utilises a proposal of expressive fuzzy knowledge representation framework called {\sf ANUIC} (Adaptive Net of Universally Interrelated Concepts). We discuss our recent achievements in taxonomy acquisition and show how even simple application of the principles of {\sf ANUIC} can improve the results of initial knowledge extraction methods.
ER -
NOVÁČEK, Vít. Imprecise Empirical Ontology Refinement: Application to Taxonomy Acquisition. In \textit{Proceedings of ICEIS 2007, vol. Artificial Intelligence and Decision Support Systems}. Portugal: INSTICC, 2007, s.~31-38. ISBN~978-972-8865-89-4.
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