• 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