14,741 research outputs found
Approximation and Difference in Description Logics
Approximation is a new inference service in Description Logics first mentioned by Baader, Küsters, and Molitor. Approximating a concept, defined in one Description Logic, means to translate this concept to another concept, defined in a second typically less expressive Description Logic, such that both concepts are as closely related as possible with respect to subsumption. The present paper provides the first in-depth investigation of this inference task. We prove that approximations from the Description Logic ALC to ALE always exist and propose an algorithm computing them. As a measure for the accuracy of the approximation, we introduce a syntax-oriented difference operator, which yields a concept description that contains all aspects of the approximated concept that are not present in the approximation. It is also argued that a purely semantical difference operator, as introduced by Teege, is less suited for this purpose. Finally, for the logics under consideration, we propose an algorithm computing the difference
A Semantic Similarity Measure for Expressive Description Logics
A totally semantic measure is presented which is able to calculate a
similarity value between concept descriptions and also between concept
description and individual or between individuals expressed in an expressive
description logic. It is applicable on symbolic descriptions although it uses a
numeric approach for the calculus. Considering that Description Logics stand as
the theoretic framework for the ontological knowledge representation and
reasoning, the proposed measure can be effectively used for agglomerative and
divisional clustering task applied to the semantic web domain.Comment: 13 pages, Appeared at CILC 2005, Convegno Italiano di Logica
Computazionale also available at
http://www.disp.uniroma2.it/CILC2005/downloads/papers/15.dAmato_CILC05.pd
Syntactic vs. Semantic Locality: How Good Is a Cheap Approximation?
Extracting a subset of a given OWL ontology that captures all the ontology's
knowledge about a specified set of terms is a well-understood task. This task
can be based, for instance, on locality-based modules (LBMs). These come in two
flavours, syntactic and semantic, and a syntactic LBM is known to contain the
corresponding semantic LBM. For syntactic LBMs, polynomial extraction
algorithms are known, implemented in the OWL API, and being used. In contrast,
extracting semantic LBMs involves reasoning, which is intractable for OWL 2 DL,
and these algorithms had not been implemented yet for expressive ontology
languages. We present the first implementation of semantic LBMs and report on
experiments that compare them with syntactic LBMs extracted from real-life
ontologies. Our study reveals whether semantic LBMs are worth the additional
extraction effort, compared with syntactic LBMs
Semantic Matchmaking as Non-Monotonic Reasoning: A Description Logic Approach
Matchmaking arises when supply and demand meet in an electronic marketplace,
or when agents search for a web service to perform some task, or even when
recruiting agencies match curricula and job profiles. In such open
environments, the objective of a matchmaking process is to discover best
available offers to a given request. We address the problem of matchmaking from
a knowledge representation perspective, with a formalization based on
Description Logics. We devise Concept Abduction and Concept Contraction as
non-monotonic inferences in Description Logics suitable for modeling
matchmaking in a logical framework, and prove some related complexity results.
We also present reasonable algorithms for semantic matchmaking based on the
devised inferences, and prove that they obey to some commonsense properties.
Finally, we report on the implementation of the proposed matchmaking framework,
which has been used both as a mediator in e-marketplaces and for semantic web
services discovery
Reasoning about exceptions in ontologies: from the lexicographic closure to the skeptical closure
Reasoning about exceptions in ontologies is nowadays one of the challenges
the description logics community is facing. The paper describes a preferential
approach for dealing with exceptions in Description Logics, based on the
rational closure. The rational closure has the merit of providing a simple and
efficient approach for reasoning with exceptions, but it does not allow
independent handling of the inheritance of different defeasible properties of
concepts. In this work we outline a possible solution to this problem by
introducing a variant of the lexicographical closure, that we call skeptical
closure, which requires to construct a single base. We develop a bi-preference
semantics semantics for defining a characterization of the skeptical closure
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