• DocumentCode
    2931298
  • Title

    An Approach to Representing Uncertainty Rules in RuleML

  • Author

    Damásio, Carlos Viegas ; Pan, Jeff Z. ; Stoilos, Giorgos ; Straccia, Umberto

  • Author_Institution
    Centro de Inteligencia Artificial, Univ. Nova de Lisboa
  • fYear
    2006
  • fDate
    Nov. 2006
  • Firstpage
    97
  • Lastpage
    106
  • Abstract
    The RuleML initiative defines a normalized markup for expressing and exchange rules in the semantic Web. However, the syntax of the language is still limited and lacks features for representing rule-based languages capable of handling uncertainty. It is desirable to have a general extension of RuleML which accommodates major existing languages proposed in the latest two decades. The main contribution of the paper is to propose such a general extension, showing how to encode many of the existing languages in this extension. We hope this work can also provide some insights on how to cover uncertainty in the RIF framework
  • Keywords
    knowledge representation; semantic Web; uncertainty handling; RIF framework; RuleML; rule-based language representation; semantic Web; uncertainty handling; uncertainty rule represention; Councils; Encoding; Knowledge representation; Logic programming; Markup languages; Ontologies; Semantic Web; Uncertainty; Web sites; XML;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Rules and Rule Markup Languages for the Semantic Web, Second International Conference on
  • Conference_Location
    Athens, GA
  • Print_ISBN
    0-7695-2652-7
  • Type

    conf

  • DOI
    10.1109/RULEML.2006.3
  • Filename
    4032396