Self-supervised Product Title Rewrite for Product Listing Ads

被引:0
作者
Zhao, Xue [1 ]
Liu, Dayiheng [1 ]
Ding, Junwei [1 ]
Yao, Liang [1 ]
Yan, Yao [1 ]
Wang, Huibo [1 ]
Yao, Wenqing [1 ]
机构
[1] Alibaba Grp, Hangzhou, Peoples R China
来源
2022 CONFERENCE OF THE NORTH AMERICAN CHAPTER OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, NAACL-HLT 2022 | 2022年
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Product Listing Ads (PLAs) are primary online advertisements merchants pay to attract more customers. However, merchants prefer to stack various attributes to the title and neglect the fluency and information priority. These seller-created titles are not suitable for PLAs as they fail to highlight the core information in the visible part in PLAs titles. In this work, we present a title rewrite solution. Specifically, we train a self-supervised language model to generate high-quality titles in terms of fluency and information priority. Extensive offline test and real-world online test have demonstrated that our solution is effective in reducing the cost and gaining more profit as it lowers our CPC1, CPB2 while improving CTR3 in the online test by a large margin. It is also easy to train and deploy, which can be a best practice of title optimization for PLAs.
引用
收藏
页码:79 / 85
页数:7
相关论文
共 8 条
[1]  
de Souza Jose GC, 2018, INLG, P233
[2]  
Dongwook Lee, 2019, arXiv
[3]  
Lewis M., 2020, ACL ASS COMP LING
[4]  
Liu DYH, 2021, Arxiv, DOI arXiv:2011.11928
[5]  
Qi WZ, 2020, FINDINGS OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, EMNLP 2020, P2401
[6]  
Radford A., 2019, Technical report, V1, P9
[7]   Controllable and Diverse Text Generation in E-commerce [J].
Shao, Huajie ;
Wang, Jun ;
Lin, Haohong ;
Zhang, Xuezhou ;
Zhang, Aston ;
Ji, Heng ;
Abdelzaher, Tarek .
PROCEEDINGS OF THE WORLD WIDE WEB CONFERENCE 2021 (WWW 2021), 2021, :2392-2401
[8]  
Zhang JG, 2019, 2019 CONFERENCE OF THE NORTH AMERICAN CHAPTER OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS: HUMAN LANGUAGE TECHNOLOGIES(NAACL HLT 2019), VOL. 2 (INDUSTRY PAPERS), P64