UNBBAYES-MEBN: COMMENTS ON IMPLEMENTING A PROBABILISTIC ONTOLOGY TOOL
Author(s):
Rommel N. Carvalho,
Marcelo Ladeira,
Laécio L. Santos,
Shou Matsumoto,
Paulo C. G. Costa
Paper abstract: The quest for principled approaches to represent and reason under uncertainty in the Semantic Web (SW) is a very active
research subject. Recently, the World Wide Web Consortium (W3C) created the Uncertainty Reasoning for the World
Wide Web Incubator Group - URW3-XG [Laskey, K.J. et al., 2007] to better define the challenge of reasoning with and
representing uncertain information available through the World Wide Web and related WWW technologies. One of the
most promising approaches is the use of a Bayesian framework to handle uncertainty in SW ontologies. Working within
this approach, Costa [2005] proposed a probabilistic ontology language, denoted PR-OWL, to represent and to reason
with probabilistic ontologies. PR-OWL language is based on MEBN – Multi-Entity Bayesian Network [Laskey &
Mahoney, 1997; Laskey & Costa, 2005; Laskey, 2007], a formalism that brings together the expressiveness of first-order
logic (FOL) and the inferential power of Bayesian Networks (BN) to support probabilistic reasoning. Since both MEBN
and PR-OWL are still under development, there is no tool that implements MEBN/PR-OWL as a knowledge
representation formalism and probabilistic reasoner. This paper discusses the technical problems encountered, as well as
how they were addressed in such an implementation that is currently under development at the University of Brasilia,
with technical support from the C4I Center at George Mason University.
