Stick to the Facts: Learning towards a Fidelity-oriented E-Commerce Product Description Generation

IJCNLP 2019 Zhangming ChanXiuying ChenYongliang WangJuntao LiZhiqiang ZhangKun GaiDongyan ZhaoRui Yan

Different from other text generation tasks, in product description generation, it is of vital importance to generate faithful descriptions that stick to the product attribute information. However, little attention has been paid to this problem... (read more)

PDF Abstract


No code implementations yet. Submit your code now

Results from the Paper

  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper

🤖 No Methods Found Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet