In logic programming the distribution semantics is one of the most popular approaches for dealing with uncertain information. In this paper we apply the distribution semantics to the Datalog+/- language that is grounded in logic programming and allows tractable ontology querying. In the resulting semantics, called DISPONTE, formulas of a probabilistic ontology can be annotated with an epistemic or a statistical probability. The epistemic probability represents a degree of confidence in the formula, while the statistical probability considers the populations to which the formula is applied. The probability of a query is defined in terms of finite set of finite explanations for the query. We also compare the DISPONTE approach for Datalog+/- ontologies with that of Probabilistic Datalog+/- where an ontology is composed of a Datalog+/- theory whose formulas are associated to an assignment of values for the random variables of a companion Markov Logic Network.

Probabilistic Ontologies in Datalog+/-

RIGUZZI, Fabrizio;BELLODI, Elena;LAMMA, Evelina
2012

Abstract

In logic programming the distribution semantics is one of the most popular approaches for dealing with uncertain information. In this paper we apply the distribution semantics to the Datalog+/- language that is grounded in logic programming and allows tractable ontology querying. In the resulting semantics, called DISPONTE, formulas of a probabilistic ontology can be annotated with an epistemic or a statistical probability. The epistemic probability represents a degree of confidence in the formula, while the statistical probability considers the populations to which the formula is applied. The probability of a query is defined in terms of finite set of finite explanations for the query. We also compare the DISPONTE approach for Datalog+/- ontologies with that of Probabilistic Datalog+/- where an ontology is composed of a Datalog+/- theory whose formulas are associated to an assignment of values for the random variables of a companion Markov Logic Network.
2012
Probabilistic Logic Programming; Datalog; Datalog+/-; Probabilistic Ontologies; Distribution Semantics
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/1672480
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