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アイテム
Hierarchical Label Generation for Text Classification
http://hdl.handle.net/10061/0002000461
http://hdl.handle.net/10061/0002000461aa44bbeb-f04c-4eca-8538-89cc750f498f
| 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 | ||||||||||||
| タイトル | Hierarchical Label Generation for Text Classification | |||||||||||
| 言語 | ||||||||||||
| 言語 | eng | |||||||||||
| 資源タイプ | ||||||||||||
| 資源タイプ | conference paper | |||||||||||
| アクセス権 | ||||||||||||
| アクセス権 | open access | |||||||||||
| 著者 |
Kwon, Jingun
× Kwon, Jingun
× 上垣外, 英剛× Song, Young-In
× Okumura, Manabu
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| 抄録 | ||||||||||||
| 内容記述タイプ | Abstract | |||||||||||
| 内容記述 | Hierarchical text classification (HTC) aims to assign the most relevant labels with the hierarchical structure to an input text. However, handling unseen labels with considering a label hierarchy is still an open problem for real-world applications because traditional HTC models employ a pre-defined label set. To deal with this problem, we propose a generation-based classifier that leverages a Seq2Seq framework to capture a label hierarchy and unseen labels explicitly. Because of no available social media datasets that target at HTC, we constructed a new (Blog) dataset using pairs of social media posts and their hierarchical topic labels. Experimental results on the Blog dataset showed the effectiveness of our generation-based classifier over state-of-the-art baseline models. Human evaluation results showed that the quality of generated unseen labels outperforms even the gold labels. | |||||||||||
| 書誌情報 |
en : Findings of the Association for Computational Linguistics: EACL 2023 p. 625-632, 発行日 2023-05-02 |
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| 会議情報 | ||||||||||||
| 会議名 | Findings of the Association for Computational Linguistics: EACL 2023 | |||||||||||
| 開始年 | 2023 | |||||||||||
| 開始月 | 05 | |||||||||||
| 開始日 | 02 | |||||||||||
| 終了年 | 2023 | |||||||||||
| 終了月 | 05 | |||||||||||
| 終了日 | 06 | |||||||||||
| 開催地 | Dubrovnik | |||||||||||
| 開催国 | HRV | |||||||||||
| 出版者 | ||||||||||||
| 出版者 | Association for Computational Linguistics | |||||||||||
| 出版者版DOI | ||||||||||||
| 関連タイプ | isReplacedBy | |||||||||||
| 識別子タイプ | DOI | |||||||||||
| 関連識別子 | https://doi.org/10.18653/v1/2023.findings-eacl.46 | |||||||||||
| 出版者版URI | ||||||||||||
| 関連タイプ | isReplacedBy | |||||||||||
| 識別子タイプ | URI | |||||||||||
| 関連識別子 | https://aclanthology.org/2023.findings-eacl.46/ | |||||||||||
| 権利 | ||||||||||||
| 権利情報Resource | http://creativecommons.org/licenses/by/4.0/ | |||||||||||
| 権利情報 | $00A92023 Association for Computational Linguistics | |||||||||||
| 著者版フラグ | ||||||||||||
| 出版タイプ | NA | |||||||||||
