Multiple News Headlines Generation using Page Metadata

Kango Iwama, Yoshinobu Kano


Abstract
Multiple headlines of a newspaper article have an important role to express the content of the article accurately and concisely. A headline depends on the content and intent of their article. While a single headline expresses the whole corresponding article, each of multiple headlines expresses different information individually. We suggest automatic generation method of such a diverse multiple headlines in a newspaper. Our generation method is based on the Pointer-Generator Network, using page metadata on a newspaper which can change headline generation behavior. This page metadata includes headline location, headline size, article page number, etc. In a previous related work, ensemble of three different generation models was performed to obtain a single headline, where each generation model generates a single headline candidate. In contrast, we use a single model to generate multiple headlines. We conducted automatic evaluations for generated headlines. The results show that our method improved ROUGE-1 score by 4.32 points higher than baseline. These results suggest that our model using page metadata can generate various multiple headlines for an article In better performance.
Anthology ID:
W19-8612
Volume:
Proceedings of the 12th International Conference on Natural Language Generation
Month:
October–November
Year:
2019
Address:
Tokyo, Japan
Editors:
Kees van Deemter, Chenghua Lin, Hiroya Takamura
Venue:
INLG
SIG:
SIGGEN
Publisher:
Association for Computational Linguistics
Note:
Pages:
101–105
Language:
URL:
https://aclanthology.org/W19-8612
DOI:
10.18653/v1/W19-8612
Bibkey:
Cite (ACL):
Kango Iwama and Yoshinobu Kano. 2019. Multiple News Headlines Generation using Page Metadata. In Proceedings of the 12th International Conference on Natural Language Generation, pages 101–105, Tokyo, Japan. Association for Computational Linguistics.
Cite (Informal):
Multiple News Headlines Generation using Page Metadata (Iwama & Kano, INLG 2019)
Copy Citation:
PDF:
https://aclanthology.org/W19-8612.pdf