Cross-Language Ontology Alignment Utilizing Machine Translation Models

  • Antonis Koukourikos
  • Pythagoras Karampiperis
  • Giannis Stoitsis
Part of the Communications in Computer and Information Science book series (CCIS, volume 390)


In the context of ontology alignment, linguistic analysis is a prominent solution, used by various proposed methodologies. When mapping ontologies that use the same language, the existent approaches have been shown to produce significant results, being able to handle complex descriptions of the enclosed concepts and properties. In order to expand the applied linguistic methods in a cross-language context, i.e. to align ontologies that use different languages, it is essential to automate the process of finding lexical correspondences, beyond simple term translation, between the entity descriptions provided by the involved ontologies. The present paper proposes a machine learning approach to obtain the optimal from a set of translation provided by different automated machine translation services, in order to use it as the basis for aligning ontology pairs that provide complex descriptions expressed in different languages.


Ontology Alignment Cross-language Alignment Automated Machine Translation Machine Learning 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Antonis Koukourikos
    • 1
  • Pythagoras Karampiperis
    • 1
  • Giannis Stoitsis
    • 2
    • 3
  1. 1.Software and Knowledge Engineering Laboratory, Institute of Informatics and TelecommunicationsNational Center for Scientific Research “Demokritos”Agia Paraskevi AttikisAthensGreece
  2. 2.Agro-Know TechnologiesAthensGreece
  3. 3.Computer Science DepartmentUniversidad de AlcalaAlcala de HenaresSpain

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