Paper Info
Title
Concept Induction in Description Logics Using Information-Theoretic Heuristics
Abstract
This paper presents an approach to ontology construction pursued through the induction of concept descriptions expressed in Description Logics. The author surveys the theoretical foundations of the standard representations for formal ontologies in the Semantic Web. After stating the learning problem in this peculiar context, a FOIL-like algorithm is presented that can be applied to learn DL concept descriptions. The algorithm performs a search through a space of candidate concept definitions by means of refinement operators. This process is guided by heuristics that are based on the available examples. The author discusses related theoretical aspects of learning with the inherent incompleteness underlying the semantics of this representation. The experimental evaluation of the system DL-Foil, which implements the learning algorithm, was carried out in two series of sessions on real ontologies from standard repositories for different domains expressed in diverse description logics.
Year
DOI
Venue
2011
10.4018/jswis.2011040102
Int. J. Semantic Web Inf. Syst.
Keywords
DocType
Volume
concept induction,standard repository,dl concept description,author survey,standard representation,concept description,information-theoretic heuristics,theoretical aspect,candidate concept definition,foil-like algorithm,theoretical foundation,description logics
Journal
7
Issue
ISSN
Citations 
2
1552-6283
3
PageRank 
References 
Authors
0.40
28
1
Name
Order
Citations
PageRank
Nicola Fanizzi1112490.54