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    <titleInfo>
        <title>SB@GU at the Complex Word Identification 2018 Shared Task</title>
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    <name type="personal">
        <namePart type="given">David</namePart>
        <namePart type="family">Alfter</namePart>
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    <name type="personal">
        <namePart type="given">Ildikó</namePart>
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            <title>Proceedings of the Thirteenth Workshop on Innovative Use of NLP for Building Educational Applications</title>
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        <name type="personal">
            <namePart type="given">Joel</namePart>
            <namePart type="family">Tetreault</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Jill</namePart>
            <namePart type="family">Burstein</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Ekaterina</namePart>
            <namePart type="family">Kochmar</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Claudia</namePart>
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        <name type="personal">
            <namePart type="given">Helen</namePart>
            <namePart type="family">Yannakoudakis</namePart>
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    <abstract>In this paper, we describe our experiments for the Shared Task on Complex Word Identification (CWI) 2018 (Yimam et al., 2018), hosted by the 13th Workshop on Innovative Use of NLP for Building Educational Applications (BEA) at NAACL 2018. Our system for English builds on previous work for Swedish concerning the classification of words into proficiency levels. We investigate different features for English and compare their usefulness using feature selection methods. For the German, Spanish and French data we use simple systems based on character n-gram models and show that sometimes simple models achieve comparable results to fully feature-engineered systems.</abstract>
    <identifier type="citekey">alfter-pilan-2018-sb</identifier>
    <identifier type="doi">10.18653/v1/W18-0537</identifier>
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        <url>https://aclanthology.org/W18-0537/</url>
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%0 Conference Proceedings
%T SB@GU at the Complex Word Identification 2018 Shared Task
%A Alfter, David
%A Pilán, Ildikó
%Y Tetreault, Joel
%Y Burstein, Jill
%Y Kochmar, Ekaterina
%Y Leacock, Claudia
%Y Yannakoudakis, Helen
%S Proceedings of the Thirteenth Workshop on Innovative Use of NLP for Building Educational Applications
%D 2018
%8 June
%I Association for Computational Linguistics
%C New Orleans, Louisiana
%F alfter-pilan-2018-sb
%X In this paper, we describe our experiments for the Shared Task on Complex Word Identification (CWI) 2018 (Yimam et al., 2018), hosted by the 13th Workshop on Innovative Use of NLP for Building Educational Applications (BEA) at NAACL 2018. Our system for English builds on previous work for Swedish concerning the classification of words into proficiency levels. We investigate different features for English and compare their usefulness using feature selection methods. For the German, Spanish and French data we use simple systems based on character n-gram models and show that sometimes simple models achieve comparable results to fully feature-engineered systems.
%R 10.18653/v1/W18-0537
%U https://aclanthology.org/W18-0537/
%U https://doi.org/10.18653/v1/W18-0537
%P 315-321

Markdown (Informal)

[SB@GU at the Complex Word Identification 2018 Shared Task](https://aclanthology.org/W18-0537/) (Alfter & Pilán, BEA 2018)

• SB@GU at the Complex Word Identification 2018 Shared Task (Alfter & Pilán, BEA 2018)

ACL

• David Alfter and Ildikó Pilán. 2018. SB@GU at the Complex Word Identification 2018 Shared Task. In Proceedings of the Thirteenth Workshop on Innovative Use of NLP for Building Educational Applications, pages 315–321, New Orleans, Louisiana. Association for Computational Linguistics.