The adoption of Description Logics for modeling real world domains within the Semantic Web is exponentially increased in the last years, also due to the availability of a large number of reasoning algorithms. Most of them exploit the tableau algorithm which has to manage non-determinism, a feature that is not easy to handle using procedural languages such as Java or C++. Reasoning on real world domains also requires the capability of managing probabilistic and uncertain information. We thus present TRILL, for “Tableau Reasoner for descrIption Logics in proLog” and TRILLP , for “TRILL powered by Pinpointing formulas”, which implement the tableau algorithm and return the probability of queries. TRILLP , instead of the set of explanations for a query, computes a Boolean formula representing them, speeding up the computation.

Tableau Reasoners for Probabilistic Ontologies Exploiting Logic Programming Techniques

ZESE, Riccardo
Primo
;
BELLODI, Elena;RIGUZZI, Fabrizio;LAMMA, Evelina
2015

Abstract

The adoption of Description Logics for modeling real world domains within the Semantic Web is exponentially increased in the last years, also due to the availability of a large number of reasoning algorithms. Most of them exploit the tableau algorithm which has to manage non-determinism, a feature that is not easy to handle using procedural languages such as Java or C++. Reasoning on real world domains also requires the capability of managing probabilistic and uncertain information. We thus present TRILL, for “Tableau Reasoner for descrIption Logics in proLog” and TRILLP , for “TRILL powered by Pinpointing formulas”, which implement the tableau algorithm and return the probability of queries. TRILLP , instead of the set of explanations for a query, computes a Boolean formula representing them, speeding up the computation.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/2337558
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