Motivations of Extensive Incorporation of Uncertainty in OLE
Ontologies

D 2006

Motivations of Extensive Incorporation of Uncertainty in OLE Ontologies

NOVÁČEK, Vít

Základní údaje

Originální název

Motivations of Extensive Incorporation of Uncertainty in OLE Ontologies

Název česky

Motivace extenzivniho vyuziti neurcitosti v OLE ontologiich

Autoři

NOVÁČEK, Vít (203 Česká republika, garant)

Vydání

Prague, SOFSEM 2006: Theory and Practice of Computer Science: 32nd Conference on Current Trends in Theory and Practice of Computer Science. Student Research Forum Proceedings, od s. 145-154, 10 s. 2006

Nakladatel

Institute of Computer Science, Academy of Sciences of the Czech Republic

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

10201 Computer sciences, information science, bioinformatics

Stát vydavatele

Česká republika

Utajení

není předmětem státního či obchodního tajemství

Odkazy

URL

Kód RIV

RIV/00216224:14330/06:00015291

Organizační jednotka

Fakulta informatiky

ISBN

80-903298-4-5

Klíčová slova anglicky

artificial intelligence; semantic web; ontology learning; uncertainty representation; fuzzy sets

Štítky

Artificial Intelligence, fuzzy sets, ontology learning, semantic web, uncertainty representation

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 21. 11. 2006 12:23, doc. Mgr. Bc. Vít Nováček, PhD

Anotace

ORIG CZ

V originále

Recently, the significance of uncertain information representation has become obvious in the Semantic Web community. This paper presents an ongoing research of uncertainty handling in automatically created ontologies. Proposal of a specific framework is provided. The research is related to OLE (Ontology LEarning), a project aimed at bottom-up generation a nd merging of domain specific ontologies. Formal systems that underlie the uncertai nty representation are briefly introduced. We will discuss a universal internal form at of uncertain conceptual structures in OLE then. The proposed format serves as a basis for inference tasks performed among an ontology. These topics are outlined as motivations of our future work.

Česky

Prezentace explicitniho vyuziti principu reprezentace neurcite informace v systemu OLE pro automaticke vytvareni ontologii.

Návaznosti

1ET100300419, projekt VaV

Název: Inteligentní modely, algoritmy, metody a nástroje pro vytváření sémantického webu

Investor: Akademie věd ČR, Inteligentní modely, algoritmy, metody a nástroje pro vytváření sémantického webu

Citovat

NOVÁČEK, Vít. Motivations of Extensive Incorporation of Uncertainty in OLE Ontologies. In SOFSEM 2006: Theory and Practice of Computer Science: 32nd Conference on Current Trends in Theory and Practice of Computer Science. Student Research Forum Proceedings. Prague: Institute of Computer Science, Academy of Sciences of the Czech Republic, 2006, s. 145-154. ISBN 80-903298-4-5.

@inproceedings{611604,
   author = {Nováček, Vít},
   address = {Prague},
   booktitle = {SOFSEM 2006: Theory and Practice of Computer Science: 32nd Conference on Current Trends in Theory and Practice of Computer Science. Student Research Forum Proceedings},
   keywords = {artificial intelligence; semantic web; ontology learning; uncertainty representation; fuzzy sets},
   language = {eng},
   location = {Prague},
   isbn = {80-903298-4-5},
   pages = {145-154},
   publisher = {Institute of Computer Science, Academy of Sciences of the Czech Republic},
   title = {Motivations of Extensive Incorporation of Uncertainty in OLE Ontologies},
   url = {http://nlp.fi.muni.cz/projects/ole/pubs.html},
   year = {2006}
}

TY  - JOUR
ID  - 611604
AU  - Nováček, Vít
PY  - 2006
TI  - Motivations of Extensive Incorporation of Uncertainty in OLE Ontologies
PB  - Institute of Computer Science, Academy of Sciences of the Czech Republic
CY  - Prague
SN  - 8090329845
KW  - artificial intelligence
KW  - semantic web
KW  - ontology learning
KW  - uncertainty representation
KW  - fuzzy sets
UR  - http://nlp.fi.muni.cz/projects/ole/pubs.html
N2  - Recently, the significance of uncertain information representation has become obvious in the Semantic Web community. This paper presents an ongoing research of uncertainty handling in automatically created ontologies. Proposal of a specific framework is provided. The research is related to OLE (Ontology LEarning), a project aimed at bottom-up generation a nd merging of domain specific ontologies. Formal systems that underlie the uncertai nty representation are briefly introduced. We will discuss a universal internal form at of uncertain conceptual structures in OLE then. The proposed format serves as a basis for inference tasks performed among an ontology. These topics are outlined as motivations of our future work.
ER  -

NOVÁČEK, Vít. Motivations of Extensive Incorporation of Uncertainty in OLE Ontologies. In \textit{SOFSEM 2006: Theory and Practice of Computer Science: 32nd Conference on Current Trends in Theory and Practice of Computer Science. Student Research Forum Proceedings}. Prague: Institute of Computer Science, Academy of Sciences of the Czech Republic, 2006, s.~145-154. ISBN~80-903298-4-5.

Podrobný výpis o publikaci