Generating Attractive Ad Text by Facilitating the Reuse of Landing Page Expressions

Hidetaka Kamigaito, Soichiro Murakami, Peinan Zhang, Hiroya Takamura, Manabu Okumura


Abstract
Ad text generation is vital for automatic advertising in various fields through search engine advertising (SEA) to avoid the cost problem caused by laborious human efforts for creating ad texts. Even though ad creators create the landing page (LP) for advertising and we can expect its quality, conventional approaches with reinforcement learning (RL) mostly focus on advertising keywords rather than LP information. This work investigates and shows the effective usage of LP information as a reward in RL-based ad text generation through automatic and human evaluations. Our analysis of the actually generated ad text shows that LP information can be a crucial reward by appropriately scaling its value range to improve ad text generation performance.
Anthology ID:
2024.inlg-main.46
Volume:
Proceedings of the 17th International Natural Language Generation Conference
Month:
September
Year:
2024
Address:
Tokyo, Japan
Editors:
Saad Mahamood, Nguyen Le Minh, Daphne Ippolito
Venue:
INLG
SIG:
SIGGEN
Publisher:
Association for Computational Linguistics
Note:
Pages:
597–608
Language:
URL:
https://aclanthology.org/2024.inlg-main.46
DOI:
Bibkey:
Cite (ACL):
Hidetaka Kamigaito, Soichiro Murakami, Peinan Zhang, Hiroya Takamura, and Manabu Okumura. 2024. Generating Attractive Ad Text by Facilitating the Reuse of Landing Page Expressions. In Proceedings of the 17th International Natural Language Generation Conference, pages 597–608, Tokyo, Japan. Association for Computational Linguistics.
Cite (Informal):
Generating Attractive Ad Text by Facilitating the Reuse of Landing Page Expressions (Kamigaito et al., INLG 2024)
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PDF:
https://aclanthology.org/2024.inlg-main.46.pdf