Using Cross-Lingual Explicit Semantic Analysis for Improving Ontology Translation

Asooja, Kartik; Gracia, Jorge; Aggarwal, Nitish y Gómez-Pérez, A. (2012). Using Cross-Lingual Explicit Semantic Analysis for Improving Ontology Translation. En: "COLING'12", December 2012, Mumbai, India.

Descripción

Título: Using Cross-Lingual Explicit Semantic Analysis for Improving Ontology Translation
Autor/es:
  • Asooja, Kartik
  • Gracia, Jorge
  • Aggarwal, Nitish
  • Gómez-Pérez, A.
Tipo de Documento: Ponencia en Congreso o Jornada (Artículo)
Título del Evento: COLING'12
Fechas del Evento: December 2012
Lugar del Evento: Mumbai, India
Título del Libro: Proc. of the Second Workshop on Applying Machine Learning Techniques to Optimise the Division of Labour in Hybrid MT
Fecha: Diciembre 2012
Materias:
Palabras Clave Informales: Ontology Translation, Word-Sense Disambiguation, Statistical Machine translation, Explicit Semantic Analysis, Ontology Localisation.
Escuela: Facultad de Informática (UPM) [antigua denominación]
Departamento: Inteligencia Artificial
Grupo Investigación UPM: oeg
Licencias Creative Commons: Ninguna

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Resumen

Semantic Web aims to allow machines to make inferences using the explicit conceptualisations contained in ontologies. By pointing to ontologies, Semantic Web-based applications are able to inter-operate and share common information easily. Nevertheless, multilingual semantic applications are still rare, owing to the fact that most online ontologies are monolingual in English. In order to solve this issue, techniques for ontology localisation and translation are needed. However, traditional machine translation is difficult to apply to ontologies, owing to the fact that ontology labels tend to be quite short in length and linguistically different from the free text paradigm. In this paper, we propose an approach to enhance machine translation of ontologies based on exploiting the well-structured concept descriptions contained in the ontology. In particular, our approach leverages the semantics contained in the ontology by using Cross Lingual Explicit Semantic Analysis (CLESA) for context-based disambiguation in phrase-based Statistical Machine Translation (SMT). The presented work is novel in the sense that application of CLESA in SMT has not been performed earlier to the best of our knowledge.

Más información

ID de Registro: 14474
Identificador DC: http://oa.upm.es/14474/
Identificador OAI: oai:oa.upm.es:14474
Depositado por: Dr Oscar Corcho
Depositado el: 13 Feb 2013 07:33
Ultima Modificación: 21 Abr 2016 14:10
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