2,977 research outputs found
Building Rules on Top of Ontologies for the Semantic Web with Inductive Logic Programming
Building rules on top of ontologies is the ultimate goal of the logical layer
of the Semantic Web. To this aim an ad-hoc mark-up language for this layer is
currently under discussion. It is intended to follow the tradition of hybrid
knowledge representation and reasoning systems such as -log that
integrates the description logic and the function-free Horn
clausal language \textsc{Datalog}. In this paper we consider the problem of
automating the acquisition of these rules for the Semantic Web. We propose a
general framework for rule induction that adopts the methodological apparatus
of Inductive Logic Programming and relies on the expressive and deductive power
of -log. The framework is valid whatever the scope of induction
(description vs. prediction) is. Yet, for illustrative purposes, we also
discuss an instantiation of the framework which aims at description and turns
out to be useful in Ontology Refinement.
Keywords: Inductive Logic Programming, Hybrid Knowledge Representation and
Reasoning Systems, Ontologies, Semantic Web.
Note: To appear in Theory and Practice of Logic Programming (TPLP)Comment: 30 pages, 6 figure
Inductive Logic Programming in Databases: from Datalog to DL+log
In this paper we address an issue that has been brought to the attention of
the database community with the advent of the Semantic Web, i.e. the issue of
how ontologies (and semantics conveyed by them) can help solving typical
database problems, through a better understanding of KR aspects related to
databases. In particular, we investigate this issue from the ILP perspective by
considering two database problems, (i) the definition of views and (ii) the
definition of constraints, for a database whose schema is represented also by
means of an ontology. Both can be reformulated as ILP problems and can benefit
from the expressive and deductive power of the KR framework DL+log. We
illustrate the application scenarios by means of examples. Keywords: Inductive
Logic Programming, Relational Databases, Ontologies, Description Logics, Hybrid
Knowledge Representation and Reasoning Systems. Note: To appear in Theory and
Practice of Logic Programming (TPLP).Comment: 30 pages, 3 figures, 2 tables
Explaining Trained Neural Networks with Semantic Web Technologies: First Steps
The ever increasing prevalence of publicly available structured data on the
World Wide Web enables new applications in a variety of domains. In this paper,
we provide a conceptual approach that leverages such data in order to explain
the input-output behavior of trained artificial neural networks. We apply
existing Semantic Web technologies in order to provide an experimental proof of
concept
Hybrid Rules with Well-Founded Semantics
A general framework is proposed for integration of rules and external first
order theories. It is based on the well-founded semantics of normal logic
programs and inspired by ideas of Constraint Logic Programming (CLP) and
constructive negation for logic programs. Hybrid rules are normal clauses
extended with constraints in the bodies; constraints are certain formulae in
the language of the external theory. A hybrid program is a pair of a set of
hybrid rules and an external theory. Instances of the framework are obtained by
specifying the class of external theories, and the class of constraints. An
example instance is integration of (non-disjunctive) Datalog with ontologies
formalized as description logics.
The paper defines a declarative semantics of hybrid programs and a
goal-driven formal operational semantics. The latter can be seen as a
generalization of SLS-resolution. It provides a basis for hybrid
implementations combining Prolog with constraint solvers. Soundness of the
operational semantics is proven. Sufficient conditions for decidability of the
declarative semantics, and for completeness of the operational semantics are
given
05371 Abstracts Collection -- Principles and Practices of Semantic Web Reasoning
From 11.09.05 to 16.09.05, the Dagstuhl Seminar 05371 ``Principles and Practices of Semantic Web Reasoning\u27\u27 % generate automaticall was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl.
During the seminar, several participants presented their current
research, and ongoing work and open problems were discussed. Abstracts of
the presentations given during the seminar as well as abstracts of
seminar results and ideas are put together in this paper. The first section
describes the seminar topics and goals in general.
Links to extended abstracts or full papers are provided, if available
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