论文标题
基于深度学习的页面创建，用于改善电子商务有机搜索流量
Deep Learning Based Page Creation for Improving E-Commerce Organic Search Traffic
论文作者
论文摘要
有机搜索包括电子商务公司总流量的很大一部分。扩大公司对有机搜索渠道接触的一种方法是创建对客户意图的覆盖范围更广泛的着陆页。在本文中，我们提出了一个基于变压器语言模型的基于有机渠道页面管理系统，旨在提高公司对渠道的总体点击的突出性。我们的系统成功处理了数百万个新登陆页面的创建和部署过程。我们展示并讨论了最先进的语言表示方法的现实表现，并揭示了我们如何将它们视为最佳的解决方案。
Organic search comprises a large portion of the total traffic for e-commerce companies. One approach to expand company's exposure on organic search channel lies on creating landing pages having broader coverage on customer intentions. In this paper, we present a transformer language model based organic channel page management system aiming at increasing prominence of the company's overall clicks on the channel. Our system successfully handles the creation and deployment process of millions of new landing pages. We show and discuss the real-world performances of state-of-the-art language representation learning method, and reveal how we find them as the production-optimal solutions.
