@inproceedings{qin-etal-2018-automatic,
title = "Automatic Article Commenting: the Task and Dataset",
author = "Qin, Lianhui and
Liu, Lemao and
Bi, Wei and
Wang, Yan and
Liu, Xiaojiang and
Hu, Zhiting and
Zhao, Hai and
Shi, Shuming",
editor = "Gurevych, Iryna and
Miyao, Yusuke",
booktitle = "Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)",
month = jul,
year = "2018",
address = "Melbourne, Australia",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/P18-2025/",
doi = "10.18653/v1/P18-2025",
pages = "151--156",
abstract = "Comments of online articles provide extended views and improve user engagement. Automatically making comments thus become a valuable functionality for online forums, intelligent chatbots, etc. This paper proposes the new task of automatic article commenting, and introduces a large-scale Chinese dataset with millions of real comments and a human-annotated subset characterizing the comments' varying quality. Incorporating the human bias of comment quality, we further develop automatic metrics that generalize a broad set of popular reference-based metrics and exhibit greatly improved correlations with human evaluations."
}
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<abstract>Comments of online articles provide extended views and improve user engagement. Automatically making comments thus become a valuable functionality for online forums, intelligent chatbots, etc. This paper proposes the new task of automatic article commenting, and introduces a large-scale Chinese dataset with millions of real comments and a human-annotated subset characterizing the comments’ varying quality. Incorporating the human bias of comment quality, we further develop automatic metrics that generalize a broad set of popular reference-based metrics and exhibit greatly improved correlations with human evaluations.</abstract>
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%0 Conference Proceedings
%T Automatic Article Commenting: the Task and Dataset
%A Qin, Lianhui
%A Liu, Lemao
%A Bi, Wei
%A Wang, Yan
%A Liu, Xiaojiang
%A Hu, Zhiting
%A Zhao, Hai
%A Shi, Shuming
%Y Gurevych, Iryna
%Y Miyao, Yusuke
%S Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
%D 2018
%8 July
%I Association for Computational Linguistics
%C Melbourne, Australia
%F qin-etal-2018-automatic
%X Comments of online articles provide extended views and improve user engagement. Automatically making comments thus become a valuable functionality for online forums, intelligent chatbots, etc. This paper proposes the new task of automatic article commenting, and introduces a large-scale Chinese dataset with millions of real comments and a human-annotated subset characterizing the comments’ varying quality. Incorporating the human bias of comment quality, we further develop automatic metrics that generalize a broad set of popular reference-based metrics and exhibit greatly improved correlations with human evaluations.
%R 10.18653/v1/P18-2025
%U https://aclanthology.org/P18-2025/
%U https://doi.org/10.18653/v1/P18-2025
%P 151-156
Markdown (Informal)
[Automatic Article Commenting: the Task and Dataset](https://aclanthology.org/P18-2025/) (Qin et al., ACL 2018)
ACL
- Lianhui Qin, Lemao Liu, Wei Bi, Yan Wang, Xiaojiang Liu, Zhiting Hu, Hai Zhao, and Shuming Shi. 2018. Automatic Article Commenting: the Task and Dataset. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 151–156, Melbourne, Australia. Association for Computational Linguistics.