DocumentCode
2950089
Title
Probabilistic ontologies and probabilistic ontology learning: Significance and challenges
Author
Foudeh, Pouya ; Salim, Naomie
Author_Institution
Fac. of Comput. Sci. & Inf. Syst., Univ. Teknol. Malaysia, Skudai, Malaysia
fYear
2011
fDate
23-24 Nov. 2011
Firstpage
1
Lastpage
4
Abstract
Human knowledge is limited therefore some information is incomplete or contradictory. When we develop an ontology, using an automatic ontology learning system or by human, with such information, the ontology would be inconsistent or we need to manage uncertain information. In non probabilistic approach, system discovers inconsistencies and then eliminates some parts of ontology to make it consistent. On the other hand, in probabilistic approach, discrepancies are adapted in the ontology.
Keywords
inference mechanisms; learning (artificial intelligence); ontologies (artificial intelligence); probability; automatic ontology learning system; ontology reasoning; probabilistic ontology learning; Bayesian methods; Cognition; Humans; Learning systems; Microstrip; Ontologies; Probabilistic logic; Probabilistic ontologies; ontology leaning; ontology reasoning; reasoning about uncertainities;
fLanguage
English
Publisher
ieee
Conference_Titel
Research and Innovation in Information Systems (ICRIIS), 2011 International Conference on
Conference_Location
Kuala Lumpur
Print_ISBN
978-1-61284-295-0
Type
conf
DOI
10.1109/ICRIIS.2011.6125727
Filename
6125727
Link To Document