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        <title>Jointly Learning Author and Annotated Character N-gram Embeddings: A Case Study in Literary Text</title>
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        <namePart type="given">Suraj</namePart>
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    <name type="personal">
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    <abstract>An author’s way of presenting a story through his/her writing style has a great impact on whether the story will be liked by readers or not. In this paper, we learn representations for authors of literary texts together with representations for character n-grams annotated with their functional roles. We train a neural character n-gram based language model using an external corpus of literary texts and transfer learned representations for use in downstream tasks. We show that augmenting the knowledge from external works of authors produces results competitive with other style-based methods for book likability prediction, genre classification, and authorship attribution.</abstract>
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%0 Conference Proceedings
%T Jointly Learning Author and Annotated Character N-gram Embeddings: A Case Study in Literary Text
%A Maharjan, Suraj
%A Mave, Deepthi
%A Shrestha, Prasha
%A Montes, Manuel
%A González, Fabio A.
%A Solorio, Thamar
%Y Mitkov, Ruslan
%Y Angelova, Galia
%S Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)
%D 2019
%8 September
%I INCOMA Ltd.
%C Varna, Bulgaria
%F maharjan-etal-2019-jointly
%X An author’s way of presenting a story through his/her writing style has a great impact on whether the story will be liked by readers or not. In this paper, we learn representations for authors of literary texts together with representations for character n-grams annotated with their functional roles. We train a neural character n-gram based language model using an external corpus of literary texts and transfer learned representations for use in downstream tasks. We show that augmenting the knowledge from external works of authors produces results competitive with other style-based methods for book likability prediction, genre classification, and authorship attribution.
%R 10.26615/978-954-452-056-4_080
%U https://aclanthology.org/R19-1080
%U https://doi.org/10.26615/978-954-452-056-4_080
%P 684-692

Markdown (Informal)

[Jointly Learning Author and Annotated Character N-gram Embeddings: A Case Study in Literary Text](https://aclanthology.org/R19-1080) (Maharjan et al., RANLP 2019)

• Jointly Learning Author and Annotated Character N-gram Embeddings: A Case Study in Literary Text (Maharjan et al., RANLP 2019)

ACL

• Suraj Maharjan, Deepthi Mave, Prasha Shrestha, Manuel Montes, Fabio A. González, and Thamar Solorio. 2019. Jointly Learning Author and Annotated Character N-gram Embeddings: A Case Study in Literary Text. In Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019), pages 684–692, Varna, Bulgaria. INCOMA Ltd..