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    <titleInfo>
        <title>Bootstrapping a Romanian Corpus for Medical Named Entity Recognition</title>
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    <name type="personal">
        <namePart type="given">Maria</namePart>
        <namePart type="family">Mitrofan</namePart>
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            <title>Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2017</title>
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        <name type="personal">
            <namePart type="given">Ruslan</namePart>
            <namePart type="family">Mitkov</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Galia</namePart>
            <namePart type="family">Angelova</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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            <publisher>INCOMA Ltd.</publisher>
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    <abstract>Named Entity Recognition (NER) is an important component of natural language processing (NLP), with applicability in biomedical domain, enabling knowledge-discovery from medical texts. Due to the fact that for the Romanian language there are only a few linguistic resources specific to the biomedical domain, it was created a sub-corpus specific to this domain. In this paper we present a newly developed Romanian sub-corpus for medical-domain NER, which is a valuable asset for the field of biomedical text processing. We provide a description of the sub-corpus, informative statistics about data-composition and we evaluate an automatic NER tool on the newly created resource.</abstract>
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    <identifier type="doi">10.26615/978-954-452-049-6_066</identifier>
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%0 Conference Proceedings
%T Bootstrapping a Romanian Corpus for Medical Named Entity Recognition
%A Mitrofan, Maria
%Y Mitkov, Ruslan
%Y Angelova, Galia
%S Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2017
%D 2017
%8 September
%I INCOMA Ltd.
%C Varna, Bulgaria
%F mitrofan-2017-bootstrapping
%X Named Entity Recognition (NER) is an important component of natural language processing (NLP), with applicability in biomedical domain, enabling knowledge-discovery from medical texts. Due to the fact that for the Romanian language there are only a few linguistic resources specific to the biomedical domain, it was created a sub-corpus specific to this domain. In this paper we present a newly developed Romanian sub-corpus for medical-domain NER, which is a valuable asset for the field of biomedical text processing. We provide a description of the sub-corpus, informative statistics about data-composition and we evaluate an automatic NER tool on the newly created resource.
%R 10.26615/978-954-452-049-6_066
%U https://doi.org/10.26615/978-954-452-049-6_066
%P 501-509

Markdown (Informal)

[Bootstrapping a Romanian Corpus for Medical Named Entity Recognition](https://doi.org/10.26615/978-954-452-049-6_066) (Mitrofan, RANLP 2017)

• Bootstrapping a Romanian Corpus for Medical Named Entity Recognition (Mitrofan, RANLP 2017)

ACL

• Maria Mitrofan. 2017. Bootstrapping a Romanian Corpus for Medical Named Entity Recognition. In Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2017, pages 501–509, Varna, Bulgaria. INCOMA Ltd..