318 research outputs found
Towards Log-Linear Logics with Concrete Domains
We present (M denotes Markov logic networks) an
extension of the log-linear description logics -LL with
concrete domains, nominals, and instances. We use Markov logic networks (MLNs)
in order to find the most probable, classified and coherent
ontology from an knowledge base. In particular, we develop
a novel way to deal with concrete domains (also known as datatypes) by
extending MLN's cutting plane inference (CPI) algorithm.Comment: StarAI201
Tractable approximate deduction for OWL
Acknowledgements This work has been partially supported by the European project Marrying Ontologies and Software Technologies (EU ICT2008-216691), the European project Knowledge Driven Data Exploitation (EU FP7/IAPP2011-286348), the UK EPSRC project WhatIf (EP/J014354/1). The authors thank Prof. Ian Horrocks and Dr. Giorgos Stoilos for their helpful discussion on role subsumptions. The authors thank Rafael S. Gonçalves et al. for providing their hotspots ontologies. The authors also thank BoC-group for providing their ADOxx Metamodelling ontologies.Peer reviewedPostprin
Hypertableau Reasoning for Description Logics
We present a novel reasoning calculus for the description logic SHOIQ^+---a
knowledge representation formalism with applications in areas such as the
Semantic Web. Unnecessary nondeterminism and the construction of large models
are two primary sources of inefficiency in the tableau-based reasoning calculi
used in state-of-the-art reasoners. In order to reduce nondeterminism, we base
our calculus on hypertableau and hyperresolution calculi, which we extend with
a blocking condition to ensure termination. In order to reduce the size of the
constructed models, we introduce anywhere pairwise blocking. We also present an
improved nominal introduction rule that ensures termination in the presence of
nominals, inverse roles, and number restrictions---a combination of DL
constructs that has proven notoriously difficult to handle. Our implementation
shows significant performance improvements over state-of-the-art reasoners on
several well-known ontologies
Reasoning over Ontologies with Hidden Content: The Import-by-Query Approach
There is currently a growing interest in techniques for hiding parts of the
signature of an ontology Kh that is being reused by another ontology Kv.
Towards this goal, in this paper we propose the import-by-query framework,
which makes the content of Kh accessible through a limited query interface. If
Kv reuses the symbols from Kh in a certain restricted way, one can reason over
Kv U Kh by accessing only Kv and the query interface. We map out the landscape
of the import-by-query problem. In particular, we outline the limitations of
our framework and prove that certain restrictions on the expressivity of Kh and
the way in which Kv reuses symbols from Kh are strictly necessary to enable
reasoning in our setting. We also identify cases in which reasoning is possible
and we present suitable import-by-query reasoning algorithms
Converting Instance Checking to Subsumption: A Rethink for Object Queries over Practical Ontologies
Efficiently querying Description Logic (DL) ontologies is becoming a vital
task in various data-intensive DL applications. Considered as a basic service
for answering object queries over DL ontologies, instance checking can be
realized by using the most specific concept (MSC) method, which converts
instance checking into subsumption problems. This method, however, loses its
simplicity and efficiency when applied to large and complex ontologies, as it
tends to generate very large MSC's that could lead to intractable reasoning. In
this paper, we propose a revision to this MSC method for DL SHI, allowing it to
generate much simpler and smaller concepts that are specific-enough to answer a
given query. With independence between computed MSC's, scalability for query
answering can also be achieved by distributing and parallelizing the
computations. An empirical evaluation shows the efficacy of our revised MSC
method and the significant efficiency achieved when using it for answering
object queries
Type-elimination-based reasoning for the description logic SHIQbs using decision diagrams and disjunctive datalog
We propose a novel, type-elimination-based method for reasoning in the
description logic SHIQbs including DL-safe rules. To this end, we first
establish a knowledge compilation method converting the terminological part of
an ALCIb knowledge base into an ordered binary decision diagram (OBDD) which
represents a canonical model. This OBDD can in turn be transformed into
disjunctive Datalog and merged with the assertional part of the knowledge base
in order to perform combined reasoning. In order to leverage our technique for
full SHIQbs, we provide a stepwise reduction from SHIQbs to ALCIb that
preserves satisfiability and entailment of positive and negative ground facts.
The proposed technique is shown to be worst case optimal w.r.t. combined and
data complexity and easily admits extensions with ground conjunctive queries.Comment: 38 pages, 3 figures, camera ready version of paper accepted for
publication in Logical Methods in Computer Scienc
Consequence Based Procedure for Description Logics with Self Restriction
We present a consequence based classification procedure for the description logics with self restriction constructor. Due to the difficulty of constructing a concept inclusion model for self restriction, we use a different proof by showing that all the completion rules can simulate all the corresponding ordered resolution inferences
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
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