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    <titleInfo>
        <title>Are Cohesive Features Relevant for Text Readability Evaluation?</title>
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    <name type="personal">
        <namePart type="given">Amalia</namePart>
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    <name type="personal">
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    <name type="personal">
        <namePart type="given">Núria</namePart>
        <namePart type="family">Gala</namePart>
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    <name type="personal">
        <namePart type="given">Anne-Laure</namePart>
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            <title>Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers</title>
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            <namePart type="given">Yuji</namePart>
            <namePart type="family">Matsumoto</namePart>
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        <name type="personal">
            <namePart type="given">Rashmi</namePart>
            <namePart type="family">Prasad</namePart>
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    <abstract>This paper investigates the effectiveness of 65 cohesion-based variables that are commonly used in the literature as predictive features to assess text readability. We evaluate the efficiency of these variables across narrative and informative texts intended for an audience of L2 French learners. In our experiments, we use a French corpus that has been both manually and automatically annotated as regards to co-reference and anaphoric chains. The efficiency of the 65 variables for readability is analyzed through a correlational analysis and some modelling experiments.</abstract>
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%0 Conference Proceedings
%T Are Cohesive Features Relevant for Text Readability Evaluation?
%A Todirascu, Amalia
%A François, Thomas
%A Bernhard, Delphine
%A Gala, Núria
%A Ligozat, Anne-Laure
%Y Matsumoto, Yuji
%Y Prasad, Rashmi
%S Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers
%D 2016
%8 December
%I The COLING 2016 Organizing Committee
%C Osaka, Japan
%F todirascu-etal-2016-cohesive
%X This paper investigates the effectiveness of 65 cohesion-based variables that are commonly used in the literature as predictive features to assess text readability. We evaluate the efficiency of these variables across narrative and informative texts intended for an audience of L2 French learners. In our experiments, we use a French corpus that has been both manually and automatically annotated as regards to co-reference and anaphoric chains. The efficiency of the 65 variables for readability is analyzed through a correlational analysis and some modelling experiments.
%U https://aclanthology.org/C16-1094
%P 987-997

Markdown (Informal)

[Are Cohesive Features Relevant for Text Readability Evaluation?](https://aclanthology.org/C16-1094) (Todirascu et al., COLING 2016)

• Are Cohesive Features Relevant for Text Readability Evaluation? (Todirascu et al., COLING 2016)

ACL

• Amalia Todirascu, Thomas François, Delphine Bernhard, Núria Gala, and Anne-Laure Ligozat. 2016. Are Cohesive Features Relevant for Text Readability Evaluation?. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, pages 987–997, Osaka, Japan. The COLING 2016 Organizing Committee.