摘要
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.
原文 | American English |
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頁數 | 8 |
DOIs | |
出版狀態 | Published - 2020 |
事件 | Conference on Artificial Intelligence (AAAI), 2020 - 持續時間: 1 一月 2020 → … |
Conference
Conference | Conference on Artificial Intelligence (AAAI), 2020 |
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期間 | 1/01/20 → … |