Abstract
This paper presents a multi-view approach for term translation spotting, based on a bilingual lexicon and comparable corpora. We propose to study different levels of representation for a term: the context, the theme and the orthography. These three approaches are studied individually and combined in order to rank translation candidates. We focus our task on French-English medical terms. Experiments show a significant improvement of the classical context-based approach, with a F-score of 40.3% for the first ranked translation candidates.
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Rubino, R., Linarès, G. (2011). A Multi-view Approach for Term Translation Spotting. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2011. Lecture Notes in Computer Science, vol 6609. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19437-5_3
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DOI: https://doi.org/10.1007/978-3-642-19437-5_3
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