Rewriting Conjunctive Queries over Description Logic Knowledge Bases

Perez-Urbina, Hector; Motik, Boris; Horrocks, Ian

doi:10.1007/978-3-540-88594-8_11

Cited by 11 publications

(14 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In particular, our approach admits queries for non-simple roles. Various other approaches used reductions to Datalog in order to establish mechanisms for conjunctive query answering [17,18,19]. These works differ from the presented approach in that they focus on general conjunctive query answering for EL and EL ++ , which is known to be more complex than satisfiability checking [16].…”

Section: Discussion and Future Workmentioning

confidence: 99%

ELP: Tractable Rules for OWL 2

Krötzsch

Rudolph

Hitzler

2008

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Abstract. We introduce ELP as a decidable fragment of the Semantic Web Rule Language (SWRL) that admits reasoning in polynomial time. ELP is based on the tractable description logic EL ++ , and encompasses an extended notion of the recently proposed DL rules for that logic. Thus ELP extends EL ++ with a number of features introduced by the forthcoming OWL 2, such as disjoint roles, local reflexivity, certain range restrictions, and the universal role. We present a reasoning algorithm based on a translation of ELP to Datalog, and this translation also enables the seamless integration of DL-safe rules into ELP. While reasoning with DL-safe rules as such is already highly intractable, we show that DL-safe rules based on the Description Logic Programming (DLP) fragment of OWL 2 can be admitted in ELP without losing tractability.

show abstract

Section: Discussion and Future Workmentioning

confidence: 99%

ELP: Tractable Rules for OWL 2

Krötzsch

Rudolph

Hitzler

2008

Lecture Notes in Computer Science

View full text Add to dashboard Cite

show abstract

“…the ABox A. Our rewriting is evaluated on A in NLOGSPACE in data complexity [4], which coincides with the lower bound for CQ answering in EL in (see [17], where EL in is called DL-lite + ). In terms of combined complexity, i.e.…”

Section: Discussionmentioning

confidence: 99%

“…Query rewriting has been extensively employed in query answering under ontologies [10,16,15]. In particular, [17] presents a resolution-based query rewriting algorithm for DL-Lite+ ontologies (which is EL in ), with Linear Datalog as target language. In [3] the authors introduce a backward chaining mechanism to identify decidable classes of tuple-generating dependencies.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Query Rewriting under Linear $$\mathcal {EL}$$ Knowledge Bases

Dimartino

Calì

Poulovassilis

et al. 2016

Web Reasoning and Rule Systems

View full text Add to dashboard Cite

Abstract. With the adoption of the recent SPARQL 1.1 standard, RDF databases are capable of directly answering more expressive queries than simple conjunctive queries. In this paper we exploit such capabilities to answer conjunctive queries (CQs) under ontologies expressed in the description logic called linear EL in , a restricted form of EL. In particular, we show a query answering algorithm that rewrites a given CQ into a conjunctive regular path query (CRPQ) which, evaluated on the given instance, returns the correct answer. Our technique is based on the representation of infinite unions of CQs by non-deterministic finite-state automata. Our results achieve optimal data complexity, as well as producing rewritings straightforwardly implementable in SPARQL 1.1.

show abstract

“…Resolutionbased calculi such as paramodulation and superposition [5] have been specially designed to improve efficiency of reasoning with equality. We base our work, however, on Resolution with Free Selection, mainly because we want to extend our previous work [33] where we employed an RFS calculus to handle various sublanguages of ELHIO ¬ . Equality can be handled in RFS by treating the equality predicate ≈ just as an ordinary predicate and axiomatizing its properties by a set of clauses E T which ensures that ans(Q , K) = ans(Q , Ξ(K) ∪ E T ).…”

Section: Approach Overviewmentioning

confidence: 99%

Tractable query answering and rewriting under description logic constraints

Perez-Urbina

Motik

Horrocks

2010

Journal of Applied Logic

Self Cite

105

100

View full text Add to dashboard Cite

Answering queries over an incomplete database w.r.t. a set of constraints is an important computational task with applications in fields as diverse as information integration and metadata management in the semantic Web. Description Logics (DLs) are constraint languages that have been extensively studied with the goal of providing useful modeling constructs while keeping the query answering problem decidable. For many DLs, query answering under constraints can be solved via query rewriting: given a conjunctive query Q and a set of DL constraints T , the query Q can be transformed into a datalog query Q T that takes into account the semantic consequences of T ; then, to obtain answers to Q w.r.t. T and some (arbitrary) database instance A, one can simply evaluate Q T over A using existing (deductive) database technology, without taking T into account. In this paper, we present a novel query rewriting algorithm that handles constraints modeled in the DL ELHIO ¬ and use it to show that answering conjunctive queries in this setting is PTime-complete w.r.t. data complexity. Our algorithm deals with various description logics of the EL and DL-Lite families and is worst-case optimal w.r.t. data complexity for all of them.

show abstract

Rewriting Conjunctive Queries over Description Logic Knowledge Bases

Cited by 11 publications

References 13 publications

ELP: Tractable Rules for OWL 2

ELP: Tractable Rules for OWL 2

Query Rewriting under Linear $$\mathcal {EL}$$ Knowledge Bases

Tractable query answering and rewriting under description logic constraints

Contact Info

Product

Resources

About