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        <title>An Evolutionary Algorithm for Automatic Summarization</title>
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        <namePart type="given">Aurélien</namePart>
        <namePart type="family">Bossard</namePart>
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        <namePart type="given">Christophe</namePart>
        <namePart type="family">Rodrigues</namePart>
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        <dateIssued>2017-09</dateIssued>
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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>This paper proposes a novel method to select sentences for automatic summarization based on an evolutionary algorithm. The algorithm explores candidate summaries space following an objective function computed over ngrams probability distributions of the candidate summary and the source documents. This method does not consider a summary as a stack of independent sentences but as a whole text, and makes use of advances in unsupervised summarization evaluation. We compare this sentence extraction method to one of the best existing methods which is based on integer linear programming, and show its efficiency on three different acknowledged corpora.</abstract>
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    <identifier type="doi">10.26615/978-954-452-049-6_017</identifier>
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        <date>2017-09</date>
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%0 Conference Proceedings
%T An Evolutionary Algorithm for Automatic Summarization
%A Bossard, Aurélien
%A Rodrigues, Christophe
%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 bossard-rodrigues-2017-evolutionary
%X This paper proposes a novel method to select sentences for automatic summarization based on an evolutionary algorithm. The algorithm explores candidate summaries space following an objective function computed over ngrams probability distributions of the candidate summary and the source documents. This method does not consider a summary as a stack of independent sentences but as a whole text, and makes use of advances in unsupervised summarization evaluation. We compare this sentence extraction method to one of the best existing methods which is based on integer linear programming, and show its efficiency on three different acknowledged corpora.
%R 10.26615/978-954-452-049-6_017
%U https://doi.org/10.26615/978-954-452-049-6_017
%P 111-120

Markdown (Informal)

[An Evolutionary Algorithm for Automatic Summarization](https://doi.org/10.26615/978-954-452-049-6_017) (Bossard & Rodrigues, RANLP 2017)

• An Evolutionary Algorithm for Automatic Summarization (Bossard & Rodrigues, RANLP 2017)

ACL

• Aurélien Bossard and Christophe Rodrigues. 2017. An Evolutionary Algorithm for Automatic Summarization. In Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2017, pages 111–120, Varna, Bulgaria. INCOMA Ltd..