Contextualizing Ontologies with OntoLight A Pragmatic Approach.pdfVIP

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