Query Answering for OWL-DL with Rules

Motik, Boris; Sattler, Ulrike; Studer, Rudi

doi:10.2139/ssrn.3199246

Cited by 94 publications

(153 citation statements)

References 20 publications

Supporting

Mentioning

153

Contrasting

Order By: Relevance

“…Recently, QA problems have gained wider attention, owing partly to emerging applications in systems involving integration between formal ontological background knowledge and instance-level rule-oriented components, e.g., interaction between Description Logics and Horn rules [9], [10] in the Semantic Web's ontology-based rule layer.…”

Section: A Query-answering (Qa) Problemsmentioning

confidence: 99%

“…To illustrate application of the procedure in Section II-B and ET rules in Section V and Section VI, consider the "Tax-cut" problem discussed in [10]. This problem is to find all persons who can have discounted tax, with the knowledge that 1) any person who has two children or more can get discounted tax, 2) men and women are not the same, 3) a person's mother is always a woman, 4) Peter has a child named Paul,5) Paul is a man, and 6) Peter has a child, who is someone's mother.…”

Section: Examplementioning

confidence: 99%

See 1 more Smart Citation

Solving Query-Answering Problems for the Semantic Web Using Equivalent Transformation

Akama¹,

Nantajeewarawat²,

Koike³

2013

LNSE

View full text Add to dashboard Cite

Abstract-A query-answering problem (QA problem) is an "all-answers finding" problem concerning with finding all ground instances of a query atomic formula that are logical consequences of a given logical formula. Based on the equivalent transformation (ET) principle, we propose a general framework for solving QA problems on Description Logics, which are logical formalisms underlying the Ontology Web Language OWL-DL. To solve such a QA problem using this framework, axioms and assertions representing the background knowledge of the problem are converted into a conjunction of first-order formulas, which is further converted by meaning-preserving Skolemization into a set of extended clauses typically containing global existential quantifications of function variables. The obtained clause set is then transformed successively using ET rules until the answer set of the original problem can be readily derived. ET rules for unfolding extended clauses, for removing useless extended clauses, and for dealing with function variables are presented. Application of the framework is illustrated.

show abstract

Section: A Query-answering (Qa) Problemsmentioning

confidence: 99%

Section: Examplementioning

confidence: 99%

Solving Query-Answering Problems for the Semantic Web Using Equivalent Transformation

Akama¹,

Nantajeewarawat²,

Koike³

2013

LNSE

View full text Add to dashboard Cite

show abstract

“…They could be adopted for performing the matching task during the resource retrieval process. In [36], an algorithm for optimizing the query answering of SHIQ knowledge bases extended with DL-safe rules is proposed, by exploiting the reduction to disjunctive programs. Möller et.…”

Section: Related Workmentioning

confidence: 99%

Dl-Link: A Conceptual Clustering Algorithm for Indexing Description Logics Knowledge Bases

d’Amato

Staab

Fanizzi

et al. 2010

Int. J. Semantic Computing

View full text Add to dashboard Cite

Efficient resource retrieval is a crucial issue, particularly when semantic resource descriptions are considered which enable the exploitation of reasoning services during the retrieval process. In this context, resources are commonly retrieved by checking if each available resource description satisfies the given query. This approach becomes inefficient with the increase of available resources. We propose a method for improving the retrieval process by constructing a tree index through a new conceptual clustering method for resources expressed as class definitions or as instances of classes in ontology languages. The available resource descriptions are located at the leaf nodes of the index, while inner nodes represent intensional descriptions (generalizations) of their child nodes. The retrieval is performed by following the tree branches whose nodes satisfy the query. Query answering time may be improved as the number of retrieval steps may be O(log n) in the best case.

show abstract

“…However, the results obtained so far [20,11,18,23,27,28,10] actually constitute a very partial picture of the computational properties of systems combining DL ontologies and Datalog rules. In particular, the computational properties of systems combining DL ontologies and the class of nonrecursive Datalog rules are mostly unknown.…”

Section: Introductionmentioning

confidence: 97%

On Combining Description Logic Ontologies and Nonrecursive Datalog Rules

Rosati

2008

Web Reasoning and Rule Systems

View full text Add to dashboard Cite

Abstract. Reasoning in systems integrating Description Logics (DL) ontologies and Datalog rules is a very hard task, and previous studies have shown undecidability of reasoning in systems integrating (even very simple) DL ontologies with recursive Datalog. However, the results obtained so far constitute a very partial picture of the computational properties of systems combining DL ontologies and Datalog rules. The aim of this paper is to contribute to complete this picture, extending the computational analysis of reasoning in systems integrating ontologies and Datalog rules. More precisely, we first provide a set of decidability and complexity results for reasoning in systems combining ontologies specified in DLs and rules specified in nonrecursive Datalog (and its extensions with inequality and negation): such results identify, from the viewpoint of the expressive abilities of the two formalisms, minimal combinations of Description Logics and Datalog in which reasoning is undecidable. Then, we present new results on the decidability and complexity of the so-called restricted (or safe) integration of DL ontologies and Datalog rules. Our results show that: (1) the unrestricted interaction between DLs and Datalog is computationally very hard even in the absence of recursion in rules; (2) surprisingly, the various "safeness" restrictions, which have been defined to regain decidability of reasoning in the interaction between DLs and recursive Datalog, appear as necessary restrictions even when rules are not recursive.

show abstract

Query Answering for OWL-DL with Rules

Cited by 94 publications

References 20 publications

Solving Query-Answering Problems for the Semantic Web Using Equivalent Transformation

Solving Query-Answering Problems for the Semantic Web Using Equivalent Transformation

Dl-Link: A Conceptual Clustering Algorithm for Indexing Description Logics Knowledge Bases

On Combining Description Logic Ontologies and Nonrecursive Datalog Rules

Contact Info

Product

Resources

About