24 research outputs found
Reasoning on Multi-Relational Contextual Hierarchies via Answer Set Programming with Algebraic Measures (Extended Abstract)
This extended abstract summarizes our previous work on a defeasible extension of Description Logic (DL) for contextual reasoning. Here, we considered on the one hand the addition of multiple dimensions of defeasibility, allowing us to express for example that a rule has to be satisfied no matter the geographical context but that the rule can change in the next years. On the other hand, we showed that Answer Set Programming (ASP) especially when enhanced with algebraic measures provide a powerful tool to implement our framework and open up perspectives for the future
Knowledge Propagation in Contextualized Knowledge Repositories: an Experimental Evaluation
As the interest in the representation of context dependent knowledge in the
Semantic Web has been recognized, a number of logic based solutions have been
proposed in this regard. In our recent works, in response to this need, we
presented the description logic-based Contextualized Knowledge Repository (CKR)
framework. CKR is not only a theoretical framework, but it has been effectively
implemented over state-of-the-art tools for the management of Semantic Web
data: inference inside and across contexts has been realized in the form of
forward SPARQL-based rules over different RDF named graphs. In this paper we
present the first evaluation results for such CKR implementation. In
particular, in first experiment we study its scalability with respect to
different reasoning regimes. In a second experiment we analyze the effects of
knowledge propagation on the computation of inferences.Comment: ARCOE-Logic 2014 Workshop Notes, pp. 13-2
Defeasible Reasoning in SROEL: from Rational Entailment to Rational Closure
In this work we study a rational extension of the low complexity
description logic SROEL, which underlies the OWL EL ontology language. The
extension involves a typicality operator T, whose semantics is based on Lehmann
and Magidor's ranked models and allows for the definition of defeasible
inclusions. We consider both rational entailment and minimal entailment. We
show that deciding instance checking under minimal entailment is in general
-hard, while, under rational entailment, instance checking can be
computed in polynomial time. We develop a Datalog calculus for instance
checking under rational entailment and exploit it, with stratified negation,
for computing the rational closure of simple KBs in polynomial time.Comment: Accepted for publication on Fundamenta Informatica
OWL and Rules
The relationship between the Web Ontology Language OWL and rule-based formalisms has been the subject of many discussions and research investigations, some of them controversial. From the many attempts to reconcile the two paradigms, we present some of the newest developments. More precisely, we show which kind of rules can be modeled in the current version of OWL, and we show how OWL can be extended to incorporate rules. We finally give references to a large body of work on rules and OWL
Local Closed-World Reasoning with Description Logics under the Well-Founded Semantics
An important question for the upcoming Semantic Web is how to best combine open world ontology languages, such as the OWL-based ones, with closed world rule-based languages. One of the most mature proposals for this combination is known as hybrid MKNF knowledge bases (Motik and Rosati, 2010 [52]), and it is based on an adaptation of the Stable Model Semantics to knowledge bases consisting of ontology axioms and rules. In this paper we propose a well-founded semantics for nondisjunctive hybrid MKNF knowledge bases that promises to provide better efficiency of reasoning, and that is compatible with both the OWL-based semantics and the traditional Well-Founded Semantics for logic programs. Moreover, our proposal allows for the detection of inconsistencies, possibly occurring in tightly integrated ontology axioms and rules, with only little additional effort. We also identify tractable fragments of the resulting language
THE DATA COMPLEXITY OF DESCRIPTION LOGIC ONTOLOGIES
We analyze the data complexity of ontology-mediated querying where the
ontologies are formulated in a description logic (DL) of the ALC family and
queries are conjunctive queries, positive existential queries, or acyclic
conjunctive queries. Our approach is non-uniform in the sense that we aim to
understand the complexity of each single ontology instead of for all ontologies
formulated in a certain language. While doing so, we quantify over the queries
and are interested, for example, in the question whether all queries can be
evaluated in polynomial time w.r.t. a given ontology. Our results include a
PTime/coNP-dichotomy for ontologies of depth one in the description logic
ALCFI, the same dichotomy for ALC- and ALCI-ontologies of unrestricted depth,
and the non-existence of such a dichotomy for ALCF-ontologies. For the latter
DL, we additionally show that it is undecidable whether a given ontology admits
PTime query evaluation. We also consider the connection between PTime query
evaluation and rewritability into (monadic) Datalog