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
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;
Conference_Titel :
Research and Innovation in Information Systems (ICRIIS), 2011 International Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-61284-295-0
DOI :
10.1109/ICRIIS.2011.6125727