The Datalog query language can express several powerful recursive properties, often crucial in real-world scenarios. While answering such queries is feasible over relational databases, the picture changes dramatically when data is enriched with intensional knowledge. It is indeed well-known that answering Datalog queries is undecidable already over lightweight knowledge bases (KBs) of the DL-Lite family. To overcome this issue, we propose a new query language based on Disjunctive Datalog rules combined with a modal epistemic operator. Rules in this language interact with the queried KB exclusively via the epistemic operator, thus extracting only the information true in every model of the KB. This form of interaction is crucial for not falling into undecidability. The contribution provided by this paper is threefold. First, we illustrate the syntax and the semantics of the novel query language. Second, we study the expressive power of different fragments of our new language and compare it with Disjunctive Datalog and its variants. Third, we outline the precise data complexity of answering queries in our new language over KBs expressed in various well-known formalisms.

Epistemic Disjunctive Datalog for Querying Knowledge Bases / Cima, G.; Console, M.; Lenzerini, M.; Poggi, A.. - 37:5(2023), pp. 6280-6288. (Intervento presentato al convegno National Conference of the American Association for Artificial Intelligence tenutosi a Washington; USA) [10.1609/aaai.v37i5.25773].

Epistemic Disjunctive Datalog for Querying Knowledge Bases

Cima G.
;
Console M.
;
Lenzerini M.
;
Poggi A.
2023

Abstract

The Datalog query language can express several powerful recursive properties, often crucial in real-world scenarios. While answering such queries is feasible over relational databases, the picture changes dramatically when data is enriched with intensional knowledge. It is indeed well-known that answering Datalog queries is undecidable already over lightweight knowledge bases (KBs) of the DL-Lite family. To overcome this issue, we propose a new query language based on Disjunctive Datalog rules combined with a modal epistemic operator. Rules in this language interact with the queried KB exclusively via the epistemic operator, thus extracting only the information true in every model of the KB. This form of interaction is crucial for not falling into undecidability. The contribution provided by this paper is threefold. First, we illustrate the syntax and the semantics of the novel query language. Second, we study the expressive power of different fragments of our new language and compare it with Disjunctive Datalog and its variants. Third, we outline the precise data complexity of answering queries in our new language over KBs expressed in various well-known formalisms.
2023
National Conference of the American Association for Artificial Intelligence
disjunctive datalog; epistemic operator; query languages; query answering; computational complexity
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Epistemic Disjunctive Datalog for Querying Knowledge Bases / Cima, G.; Console, M.; Lenzerini, M.; Poggi, A.. - 37:5(2023), pp. 6280-6288. (Intervento presentato al convegno National Conference of the American Association for Artificial Intelligence tenutosi a Washington; USA) [10.1609/aaai.v37i5.25773].
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Note: DOI: https://doi.org/10.1609/aaai.v37i5.25773
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1694117
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