Cross-Lingual Ontology Mapping – An Investigation of the Impact of Machine Translation

  • Bo Fu
  • Rob Brennan
  • Declan O’Sullivan
Conference paper

DOI: 10.1007/978-3-642-10871-6_1

Part of the Lecture Notes in Computer Science book series (LNCS, volume 5926)
Cite this paper as:
Fu B., Brennan R., O’Sullivan D. (2009) Cross-Lingual Ontology Mapping – An Investigation of the Impact of Machine Translation. In: Gómez-Pérez A., Yu Y., Ding Y. (eds) The Semantic Web. ASWC 2009. Lecture Notes in Computer Science, vol 5926. Springer, Berlin, Heidelberg

Abstract

Ontologies are at the heart of knowledge management and make use of information that is not only written in English but also in many other natural languages. In order to enable knowledge discovery, sharing and reuse of these multilingual ontologies, it is necessary to support ontology mapping despite natural language barriers. This paper examines the soundness of a generic approach that involves machine translation tools and monolingual ontology matching techniques in cross-lingual ontology mapping scenarios. In particular, experimental results collected from case studies which engage mappings of independent ontologies that are labeled in English and Chinese are presented. Based on findings derived from these studies, limitations of this generic approach are discussed. It is shown with evidence that appropriate translations of conceptual labels in ontologies are of crucial importance when applying monolingual matching techniques in cross-lingual ontology mapping. Finally, to address the identified challenges, a semantic-oriented cross-lingual ontology mapping (SOCOM) framework is proposed and discussed.

Keywords

Cross-lingual Ontology Mapping Multilingual Ontologies Ontology Rendering 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Bo Fu
    • 1
  • Rob Brennan
    • 1
  • Declan O’Sullivan
    • 1
  1. 1.Centre for Next Generation Localisation & Knowledge and Data Engineering Group, School of Computer Science and StatisticsTrinity College DublinIreland

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