Authors
Mia Xu Chen, Benjamin N Lee, Gagan Bansal, Yuan Cao, Shuyuan Zhang, Justin Lu, Jackie Tsay, Yinan Wang, Andrew M Dai, Zhifeng Chen, Timothy Sohn, Yonghui Wu
Publication date
2019/7/25
Book
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining
Pages
2287-2295
Description
In this paper, we present Smart Compose, a novel system for generating interactive, real-time suggestions in Gmail that assists users in writing mails by reducing repetitive typing. In the design and deployment of such a large-scale and complicated system, we faced several challenges including model selection, performance evaluation, serving and other practical issues. At the core of Smart Compose is a large-scale neural language model. We leveraged state-of-the-art machine learning techniques for language model training which enabled high-quality suggestion prediction, and constructed novel serving infrastructure for high-throughput and real-time inference. Experimental results show the effectiveness of our proposed system design and deployment approach. This system is currently being served in Gmail.
Scholar articles
MX Chen, BN Lee, G Bansal, Y Cao, S Zhang, J Lu… - Proceedings of the 25th ACM SIGKDD International …, 2019