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        <title>Automatic Translation of Biomedical Terms by Supervised Machine Learning</title>
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    <name type="personal">
        <namePart type="given">Vincent</namePart>
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            <title>Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC’08)</title>
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            <namePart type="given">Nicoletta</namePart>
            <namePart type="family">Calzolari</namePart>
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            <namePart type="given">Khalid</namePart>
            <namePart type="family">Choukri</namePart>
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            <namePart type="given">Bente</namePart>
            <namePart type="family">Maegaard</namePart>
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            <namePart type="given">Joseph</namePart>
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            <namePart type="given">Jan</namePart>
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        <name type="personal">
            <namePart type="given">Daniel</namePart>
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    <abstract>In this paper, we present a simple yet efficient automatic system to translate biomedical terms. It mainly relies on a machine learning approach able to infer rewriting rules from pair of terms in two languages. Given a new term, these rules are then used to transform the initial term into its translation. Since conflicting rules may produce different translations, we also use language modeling to single out the best candidate. We report experiments on different language pairs (including Czech, English, French, Italian, German, Portuguese, Spanish and even Russian); our approach yields good results (varying according to the considered languages) and outperforms existing ones for the French-English pair.</abstract>
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%0 Conference Proceedings
%T Automatic Translation of Biomedical Terms by Supervised Machine Learning
%A Claveau, Vincent
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Odijk, Jan
%Y Piperidis, Stelios
%Y Tapias, Daniel
%S Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC’08)
%D 2008
%8 May
%I European Language Resources Association (ELRA)
%C Marrakech, Morocco
%F claveau-2008-automatic
%X In this paper, we present a simple yet efficient automatic system to translate biomedical terms. It mainly relies on a machine learning approach able to infer rewriting rules from pair of terms in two languages. Given a new term, these rules are then used to transform the initial term into its translation. Since conflicting rules may produce different translations, we also use language modeling to single out the best candidate. We report experiments on different language pairs (including Czech, English, French, Italian, German, Portuguese, Spanish and even Russian); our approach yields good results (varying according to the considered languages) and outperforms existing ones for the French-English pair.
%U http://www.lrec-conf.org/proceedings/lrec2008/pdf/173_paper.pdf

Markdown (Informal)

[Automatic Translation of Biomedical Terms by Supervised Machine Learning](http://www.lrec-conf.org/proceedings/lrec2008/pdf/173_paper.pdf) (Claveau, LREC 2008)

• Automatic Translation of Biomedical Terms by Supervised Machine Learning (Claveau, LREC 2008)

ACL

• Vincent Claveau. 2008. Automatic Translation of Biomedical Terms by Supervised Machine Learning. In Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08), Marrakech, Morocco. European Language Resources Association (ELRA).