Abstract
In the context of the Semantic Web, resources on the net can be enriched by well-defined, machine-understandable metadata describing their associated conceptual meaning. These metadata consisting of natural language descriptions of concepts are the focus of the activity we describe in this chapter, namely, ontology localization. In the framework of the NeOn Methodology, ontology localization is defined as the activity of adapting an ontology to a particular language and culture. This adaptation mainly involves the translation of the natural language descriptions of the ontology from a source natural language to a target natural language, with the final objective of obtaining a multilingual ontology, that is, an ontology documented in several natural languages. The purpose of this chapter is to provide detailed and prescriptive methodological guidelines to support the performance of this activity.
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Notes
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Obtained on September 30, 2009, from http://www.internetworldstats.com
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In NLP, context refers to the environment in which a word is used and provides the information needed for figuring out the meaning of homonyms or polysemic words.
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The number of context labels used to disambiguate a translated label depends on the ontology domain. However, in our experiments we found that a threshold of three context labels reduce the time of response of the overall system and it is compatible with the range of good responses found by comparing the results with human evaluations.
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Mejía, M.E., Montiel-Ponsoda, E., de Cea, G.A., Gómez-Pérez, A. (2012). Ontology Localization. In: Suárez-Figueroa, M., Gómez-Pérez, A., Motta, E., Gangemi, A. (eds) Ontology Engineering in a Networked World. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24794-1_8
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