157 research outputs found
Ontology Module Extraction via Datalog Reasoning
Module extraction - the task of computing a (preferably small) fragment M of
an ontology T that preserves entailments over a signature S - has found many
applications in recent years. Extracting modules of minimal size is, however,
computationally hard, and often algorithmically infeasible. Thus, practical
techniques are based on approximations, where M provably captures the relevant
entailments, but is not guaranteed to be minimal. Existing approximations,
however, ensure that M preserves all second-order entailments of T w.r.t. S,
which is stronger than is required in many applications, and may lead to large
modules in practice. In this paper we propose a novel approach in which module
extraction is reduced to a reasoning problem in datalog. Our approach not only
generalises existing approximations in an elegant way, but it can also be
tailored to preserve only specific kinds of entailments, which allows us to
extract significantly smaller modules. An evaluation on widely-used ontologies
has shown very encouraging results.Comment: 13 pages. To appear in AAAI-1
Axiom Pinpointing
Axiom pinpointing refers to the task of finding the specific axioms in an
ontology which are responsible for a consequence to follow. This task has been
studied, under different names, in many research areas, leading to a
reformulation and reinvention of techniques. In this work, we present a general
overview to axiom pinpointing, providing the basic notions, different
approaches for solving it, and some variations and applications which have been
considered in the literature. This should serve as a starting point for
researchers interested in related problems, with an ample bibliography for
delving deeper into the details
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