TemPEST: Soft template-based personalized EDM subject generation through collaborative summarization

Yu Hsiu Chen, Pin Yu Chen, Hong-Han Shuai, Wen-Chih Peng

研究成果: Conference contribution同行評審

5 引文 斯高帕斯(Scopus)


We address personalized Electronic Direct Mail (EDM) subject generation, which generates an attractive subject line for a product description according to user’s preference on different contents or writing styles. Generating personalized EDM subjects has a few notable differences from generating text summaries. The subject has to be not only faithful to the description itself but also attractive to increase the click-through rate. Moreover, different users may have different preferences over the styles of topics. We propose a novel personalized EDM subject generation model named Soft Template-based Personalized EDM Subject Generator (TemPEST) to consider the aforementioned users’ characteristics when generating subjects, which contains a soft template-based selective encoder network, a user rating encoder network, a summary decoder network and a rating decoder. Experimental results indicate that TemPEST is able to generate personalized topics and also effectively perform recommending rating reconstruction.

主出版物標題AAAI 2020 - 34th AAAI Conference on Artificial Intelligence
發行者AAAI press
出版狀態Published - 2月 2020
事件34th AAAI Conference on Artificial Intelligence, AAAI 2020 - New York, United States
持續時間: 7 2月 202012 2月 2020


名字AAAI 2020 - 34th AAAI Conference on Artificial Intelligence


Conference34th AAAI Conference on Artificial Intelligence, AAAI 2020
國家/地區United States
城市New York