Proceedings Abstracts of the Twenty-Fourth International Joint Conference on Artificial Intelligence

Reasoning with Probabilistic Ontologies / 4310
Fabrizio Riguzzi, Elena Bellodi, Evelina Lamma, Riccardo Zese

Modeling real world domains requires ever more frequently to represent uncertain information. The DISPONTE semantics for probabilistic description logics allows to annotate axioms of a knowledge base with a value that represents their probability. In this paper we discuss approaches for performing inference from probabilistic ontologies following the DISPONTE semantics. We present the algorithm BUNDLE for computing the probability of queries. BUNDLE exploits an underlying Description Logic reasoner, such as Pellet, in order to find explanations for a query. These are then encoded in a Binary Decision Diagram that is used for computing the probability of the query.