| アイテムタイプ |
会議発表論文 / Conference Paper(1) |
| 公開日 |
2024-06-07 |
| タイトル |
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タイトル |
Joint Learning-based Heterogeneous Graph Attention Network for Timeline Summarization |
| 言語 |
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言語 |
eng |
| 資源タイプ |
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資源タイプ |
conference paper |
| アクセス権 |
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アクセス権 |
open access |
| 著者 |
You, Jingyi
Li, Dongyuan
上垣外, 英剛
Funakoshi, Kotaro
Okumura, Manabu
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| 抄録 |
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内容記述タイプ |
Abstract |
|
内容記述 |
Previous studies on the timeline summarization (TLS) task ignored the information interaction between sentences and dates, and adopted pre-defined unlearnable representations for them. They also considered date selection and event detection as two independent tasks, which makes it impossible to integrate their advantages and obtain a globally optimal summary. In this paper, we present a joint learning-based heterogeneous graph attention network for TLS (HeterTls), in which date selection and event detection are combined into a unified framework to improve the extraction accuracy and remove redundant sentences simultaneously. Our heterogeneous graph involves multiple types of nodes, the representations of which are iteratively learned across the heterogeneous graph attention layer. We evaluated our model on four datasets, and found that it significantly outperformed the current state-of-the-art baselines with regard to ROUGE scores and date selection metrics. |
| 書誌情報 |
en : Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
p. 4091-4104,
発行日 2022-07-10
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| 会議情報 |
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会議名 |
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies |
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開始年 |
2022 |
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開始月 |
07 |
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開始日 |
10 |
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終了年 |
2022 |
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終了月 |
07 |
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終了日 |
15 |
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開催地 |
Seattle |
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開催国 |
USA |
| 出版者 |
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出版者 |
Association for Computational Linguistics |
| 出版者版DOI |
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関連タイプ |
isReplacedBy |
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識別子タイプ |
DOI |
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関連識別子 |
https://doi.org/10.18653/v1/2022.naacl-main.301 |
| 出版者版URI |
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関連タイプ |
isReplacedBy |
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識別子タイプ |
URI |
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関連識別子 |
https://aclanthology.org/2022.naacl-main.301/ |
| 権利 |
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権利情報Resource |
http://creativecommons.org/licenses/by/4.0/ |
|
権利情報 |
$00A92022 Association for Computational Linguistics |
| 著者版フラグ |
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出版タイプ |
NA |
