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    <titleInfo>
        <title>Discriminating between Similar Languages using Weighted Subword Features</title>
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    <name type="personal">
        <namePart type="given">Adrien</namePart>
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            <title>Proceedings of the Fourth Workshop on NLP for Similar Languages, Varieties and Dialects (VarDial)</title>
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        <name type="personal">
            <namePart type="given">Preslav</namePart>
            <namePart type="family">Nakov</namePart>
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        <name type="personal">
            <namePart type="given">Marcos</namePart>
            <namePart type="family">Zampieri</namePart>
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        <name type="personal">
            <namePart type="given">Nikola</namePart>
            <namePart type="family">Ljubešić</namePart>
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        <name type="personal">
            <namePart type="given">Jörg</namePart>
            <namePart type="family">Tiedemann</namePart>
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        <name type="personal">
            <namePart type="given">Shevin</namePart>
            <namePart type="family">Malmasi</namePart>
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        <name type="personal">
            <namePart type="given">Ahmed</namePart>
            <namePart type="family">Ali</namePart>
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    <abstract>The present contribution revolves around a contrastive subword n-gram model which has been tested in the Discriminating between Similar Languages shared task. I present and discuss the method used in this 14-way language identification task comprising varieties of 6 main language groups. It features the following characteristics: (1) the preprocessing and conversion of a collection of documents to sparse features; (2) weighted character n-gram profiles; (3) a multinomial Bayesian classifier. Meaningful bag-of-n-grams features can be used as a system in a straightforward way, my approach outperforms most of the systems used in the DSL shared task (3rd rank).</abstract>
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%0 Conference Proceedings
%T Discriminating between Similar Languages using Weighted Subword Features
%A Barbaresi, Adrien
%Y Nakov, Preslav
%Y Zampieri, Marcos
%Y Ljubešić, Nikola
%Y Tiedemann, Jörg
%Y Malmasi, Shevin
%Y Ali, Ahmed
%S Proceedings of the Fourth Workshop on NLP for Similar Languages, Varieties and Dialects (VarDial)
%D 2017
%8 April
%I Association for Computational Linguistics
%C Valencia, Spain
%F barbaresi-2017-discriminating
%X The present contribution revolves around a contrastive subword n-gram model which has been tested in the Discriminating between Similar Languages shared task. I present and discuss the method used in this 14-way language identification task comprising varieties of 6 main language groups. It features the following characteristics: (1) the preprocessing and conversion of a collection of documents to sparse features; (2) weighted character n-gram profiles; (3) a multinomial Bayesian classifier. Meaningful bag-of-n-grams features can be used as a system in a straightforward way, my approach outperforms most of the systems used in the DSL shared task (3rd rank).
%R 10.18653/v1/W17-1223
%U https://aclanthology.org/W17-1223
%U https://doi.org/10.18653/v1/W17-1223
%P 184-189

Markdown (Informal)

[Discriminating between Similar Languages using Weighted Subword Features](https://aclanthology.org/W17-1223) (Barbaresi, VarDial 2017)

• Discriminating between Similar Languages using Weighted Subword Features (Barbaresi, VarDial 2017)

ACL

• Adrien Barbaresi. 2017. Discriminating between Similar Languages using Weighted Subword Features. In Proceedings of the Fourth Workshop on NLP for Similar Languages, Varieties and Dialects (VarDial), pages 184–189, Valencia, Spain. Association for Computational Linguistics.