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    <titleInfo>
        <title>NovelPerspective: Identifying Point of View Characters</title>
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    <name type="personal">
        <namePart type="given">Lyndon</namePart>
        <namePart type="family">White</namePart>
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        <namePart type="given">Roberto</namePart>
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    <name type="personal">
        <namePart type="given">Mohammed</namePart>
        <namePart type="family">Bennamoun</namePart>
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            <title>Proceedings of ACL 2018, System Demonstrations</title>
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    <abstract>We present NovelPerspective: a tool to allow consumers to subset their digital literature, based on point of view (POV) character. Many novels have multiple main characters each with their own storyline running in parallel. A well-known example is George R. R. Martin’s novel: “A Game of Thrones”, and others from that series. Our tool detects the main character that each section is from the POV of, and allows the user to generate a new ebook with only those sections. This gives consumers new options in how they consume their media; allowing them to pursue the storylines sequentially, or skip chapters about characters they find boring. We present two heuristic-based baselines, and two machine learning based methods for the detection of the main character.</abstract>
    <identifier type="citekey">white-etal-2018-novelperspective</identifier>
    <identifier type="doi">10.18653/v1/P18-4002</identifier>
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%0 Conference Proceedings
%T NovelPerspective: Identifying Point of View Characters
%A White, Lyndon
%A Togneri, Roberto
%A Liu, Wei
%A Bennamoun, Mohammed
%S Proceedings of ACL 2018, System Demonstrations
%D 2018
%8 jul
%I Association for Computational Linguistics
%C Melbourne, Australia
%F white-etal-2018-novelperspective
%X We present NovelPerspective: a tool to allow consumers to subset their digital literature, based on point of view (POV) character. Many novels have multiple main characters each with their own storyline running in parallel. A well-known example is George R. R. Martin’s novel: “A Game of Thrones”, and others from that series. Our tool detects the main character that each section is from the POV of, and allows the user to generate a new ebook with only those sections. This gives consumers new options in how they consume their media; allowing them to pursue the storylines sequentially, or skip chapters about characters they find boring. We present two heuristic-based baselines, and two machine learning based methods for the detection of the main character.
%R 10.18653/v1/P18-4002
%U https://aclanthology.org/P18-4002
%U https://doi.org/10.18653/v1/P18-4002
%P 7-12

Markdown (Informal)

[NovelPerspective: Identifying Point of View Characters](https://aclanthology.org/P18-4002) (White et al., ACL 2018)

• NovelPerspective: Identifying Point of View Characters (White et al., ACL 2018)

ACL

• Lyndon White, Roberto Togneri, Wei Liu, and Mohammed Bennamoun. 2018. NovelPerspective: Identifying Point of View Characters. In Proceedings of ACL 2018, System Demonstrations, pages 7–12, Melbourne, Australia. Association for Computational Linguistics.