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Contextualizing Ontologies with OntoLight A Pragmatic Approach
Contextualizing Ontologies with OntoLight: A Pragmatic
Approach
Marko Grobelnik, Janez Brank, Bla? Fortuna, Igor Mozeti?
Department of Knowledge Technologies
Jozef Stefan Institute
Jamova 39, 1000 Ljubljana, Slovenia
e-mail: {marko.grobelnik, janez.brank, blaz.fortuna, igor.mozetic}@ijs.si
ABSTRACT
We present a pragmatic approach to using large-scale
ontologies as contexts. The approach is based on a light-
weight ontology model and grounding of the ontology
concepts in textual documents. These assumptions allow
for efficient implementation of the basic operations
(classification, population and mappings between
ontologies), and, as a consequence, exploitation of
several large-scale ontologies as background, contextual
knowledge. We demonstrate one possible scenario how
contextual information can be exploited during semi-
automatic ontology construction from text corpora.
1 INTRODUCTION
Ontologies represent isolated pieces of knowledge. By
networking them, one can explore their interrelations. One
form of networked ontologies are contextualized ontologies.
In this case, one ontology represents a context of the other
and its constituent ingredients (concepts and relations). So,
for a given ontology, its ingredients can be interpreted in
different contexts by selecting appropriate ontologies which
represent appropriate contexts.
In this paper we describe OntoLight which implements basic
reasoning functionalities for contextualized ontologies. It is
limited to light-weight ontologies which are grounded with
appropriate text corpora. The representation and reasoning
scales to the largest currently available ontologies,
comprising up to one million concepts. In particular,
OntoLight currently incorporates the following five
ontologies: AgroVoc and ASFA (relevant for the Food and
Agricultural Organization of UN), EuroVoc (EU
legislation), Cyc (common-sense knowledge) and DMoz
(WWW directory).
There are two basic reaso
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