Automatic Controllable Product Copywriting for E-Commerce
This addresses the need for adaptive copywriting in e-commerce platforms to enhance user experience, though it appears incremental as it builds on existing methods like prefix-based language models.
The paper tackles the problem of generating dynamic and controllable product descriptions for e-commerce by deploying a system (EPCCG) into JD.com's platform, resulting in significant payoff from real-time integration.
Automatic product description generation for e-commerce has witnessed significant advancement in the past decade. Product copywriting aims to attract users' interest and improve user experience by highlighting product characteristics with textual descriptions. As the services provided by e-commerce platforms become diverse, it is necessary to adapt the patterns of automatically-generated descriptions dynamically. In this paper, we report our experience in deploying an E-commerce Prefix-based Controllable Copywriting Generation (EPCCG) system into the JD.com e-commerce product recommendation platform. The development of the system contains two main components: 1) copywriting aspect extraction; 2) weakly supervised aspect labeling; 3) text generation with a prefix-based language model; 4) copywriting quality control. We conduct experiments to validate the effectiveness of the proposed EPCCG. In addition, we introduce the deployed architecture which cooperates with the EPCCG into the real-time JD.com e-commerce recommendation platform and the significant payoff since deployment.