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        <title>Extractive Headline Generation Based on Learning to Rank for Community Question Answering</title>
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    <abstract>User-generated content such as the questions on community question answering (CQA) forums does not always come with appropriate headlines, in contrast to the news articles used in various headline generation tasks. In such cases, we cannot use paired supervised data, e.g., pairs of articles and headlines, to learn a headline generation model. To overcome this problem, we propose an extractive headline generation method based on learning to rank for CQA that extracts the most informative substring from each question as its headline. Experimental results show that our method outperforms several baselines, including a prefix-based method, which is widely used in real services.</abstract>
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%0 Conference Proceedings
%T Extractive Headline Generation Based on Learning to Rank for Community Question Answering
%A Higurashi, Tatsuru
%A Kobayashi, Hayato
%A Masuyama, Takeshi
%A Murao, Kazuma
%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 higurashi-etal-2018-extractive
%X User-generated content such as the questions on community question answering (CQA) forums does not always come with appropriate headlines, in contrast to the news articles used in various headline generation tasks. In such cases, we cannot use paired supervised data, e.g., pairs of articles and headlines, to learn a headline generation model. To overcome this problem, we propose an extractive headline generation method based on learning to rank for CQA that extracts the most informative substring from each question as its headline. Experimental results show that our method outperforms several baselines, including a prefix-based method, which is widely used in real services.
%U https://aclanthology.org/C18-1148
%P 1742-1753

Markdown (Informal)

[Extractive Headline Generation Based on Learning to Rank for Community Question Answering](https://aclanthology.org/C18-1148) (Higurashi et al., COLING 2018)

• Extractive Headline Generation Based on Learning to Rank for Community Question Answering (Higurashi et al., COLING 2018)

ACL

• Tatsuru Higurashi, Hayato Kobayashi, Takeshi Masuyama, and Kazuma Murao. 2018. Extractive Headline Generation Based on Learning to Rank for Community Question Answering. In Proceedings of the 27th International Conference on Computational Linguistics, pages 1742–1753, Santa Fe, New Mexico, USA. Association for Computational Linguistics.