<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="alharthi-etal-2018-authorship">
    <titleInfo>
        <title>Authorship Identification for Literary Book Recommendations</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Haifa</namePart>
        <namePart type="family">Alharthi</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Diana</namePart>
        <namePart type="family">Inkpen</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Stan</namePart>
        <namePart type="family">Szpakowicz</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2018-08</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 27th International Conference on Computational Linguistics</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Emily</namePart>
            <namePart type="given">M</namePart>
            <namePart type="family">Bender</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Leon</namePart>
            <namePart type="family">Derczynski</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Pierre</namePart>
            <namePart type="family">Isabelle</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Santa Fe, New Mexico, USA</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>Book recommender systems can help promote the practice of reading for pleasure, which has been declining in recent years. One factor that influences reading preferences is writing style. We propose a system that recommends books after learning their authors’ style. To our knowledge, this is the first work that applies the information learned by an author-identification model to book recommendations. We evaluated the system according to a top-k recommendation scenario. Our system gives better accuracy when compared with many state-of-the-art methods. We also conducted a qualitative analysis by checking if similar books/authors were annotated similarly by experts.</abstract>
    <identifier type="citekey">alharthi-etal-2018-authorship</identifier>
    <location>
        <url>https://aclanthology.org/C18-1033</url>
    </location>
    <part>
        <date>2018-08</date>
        <extent unit="page">
            <start>390</start>
            <end>400</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Authorship Identification for Literary Book Recommendations
%A Alharthi, Haifa
%A Inkpen, Diana
%A Szpakowicz, Stan
%Y Bender, Emily M.
%Y Derczynski, Leon
%Y Isabelle, Pierre
%S Proceedings of the 27th International Conference on Computational Linguistics
%D 2018
%8 August
%I Association for Computational Linguistics
%C Santa Fe, New Mexico, USA
%F alharthi-etal-2018-authorship
%X Book recommender systems can help promote the practice of reading for pleasure, which has been declining in recent years. One factor that influences reading preferences is writing style. We propose a system that recommends books after learning their authors’ style. To our knowledge, this is the first work that applies the information learned by an author-identification model to book recommendations. We evaluated the system according to a top-k recommendation scenario. Our system gives better accuracy when compared with many state-of-the-art methods. We also conducted a qualitative analysis by checking if similar books/authors were annotated similarly by experts.
%U https://aclanthology.org/C18-1033
%P 390-400

Markdown (Informal)

[Authorship Identification for Literary Book Recommendations](https://aclanthology.org/C18-1033) (Alharthi et al., COLING 2018)

• Authorship Identification for Literary Book Recommendations (Alharthi et al., COLING 2018)

ACL

• Haifa Alharthi, Diana Inkpen, and Stan Szpakowicz. 2018. Authorship Identification for Literary Book Recommendations. In Proceedings of the 27th International Conference on Computational Linguistics, pages 390–400, Santa Fe, New Mexico, USA. Association for Computational Linguistics.