PR-OWL: A Bayesian Framework for the Semantic Web
|
Permanent citation URL:
|
Files in This Item:
| Title: | PR-OWL: A Bayesian Framework for the Semantic Web |
| Author(s): | Costa, Paulo C. G.; Laskey, Kathryn B.; Laskey, Kenneth J. |
| Keywords: | PR-OWL; Probabilistic OWL; probabilistic ontologies; multi-entity Bayesian networks (MEBN); multi-entity Bayesian networks (MEBN); Semantic Web; uncertainty reasoning; Bayesian; Ontology mapping |
| Issue Date: | 7-Nov-2005 |
| Citation: | Costa, Paulo C. G.; Laskey, Kathryn B.; and Laskey, Kenneth J. (2005) PR-OWL: A Bayesian Framework for the Semantic Web. Proceedings of the first workshop on Uncertainty Reasoning for the Semantic Web (URSW 2005), held at the Fourth International Semantic Web Conference (ISWC 2004). November, 6-10 2005, Galway, Ireland. |
| Series/Report no.: | C4I-05-06 |
| Abstract: | This paper addresses a major weakness of current technologies for the Semantic Web, namely the lack of a principled means to represent and reason about uncertainty. This not only hinders the realization of the original vision for the Semantic Web, but also creates a barrier to the development of new, powerful features for general knowledge applications that require proper treatment of uncertain phenomena. We propose to extend OWL, the ontology language recommended by the World Wide Web Consortium (W3C), to provide the ability to express probabilistic knowledge. The new language, PR-OWL, will allow legacy ontologies to interoperate with newly developed probabilistic ontologies. PR-OWL will move beyond the current limitations of deterministic classical logic to a full first-order probabilistic logic. By providing a principled means of modeling uncertainty in ontologies, PR-OWL will serve as a supporting tool for many applications that can benefit from probabilistic inference within an ontology language, thus representing an important step toward the W3C’s vision for the Semantic Web. |
| URI: | http://hdl.handle.net/1920/454 |
| Appears in Collections: | C4I Papers |
Items in MARS are protected by copyright, with all rights reserved, to the extent allowed by law.