Building Task-Oriented Dialogue Systems for Online Shopping

Abstract

We present a general solution towards building task-oriented dialogue systems for online shopping, aiming to assist online customers in completing various purchase-related tasks, such as searching products and answering questions, in a natural language conversation manner. As a pioneering work, we show what & how existing NLP techniques, data resources, and crowdsourcing can be leveraged to build such task-oriented dialogue systems for E-commerce usage. To demonstrate its effectiveness, we integrate our system into a mobile online shopping app. To the best of our knowledge, this is the first time that an AI bot in Chinese is practically used in online shopping scenario with millions of real consumers. Interesting and insightful observations are shown in the experimental part, based on the analysis of human-bot conversation log. Several current challenges are also pointed out as our future directions.

Cite

Text

Yan et al. "Building Task-Oriented Dialogue Systems for Online Shopping." AAAI Conference on Artificial Intelligence, 2017. doi:10.1609/AAAI.V31I1.11182

Markdown

[Yan et al. "Building Task-Oriented Dialogue Systems for Online Shopping." AAAI Conference on Artificial Intelligence, 2017.](https://mlanthology.org/aaai/2017/yan2017aaai-building/) doi:10.1609/AAAI.V31I1.11182

BibTeX

@inproceedings{yan2017aaai-building,
  title     = {{Building Task-Oriented Dialogue Systems for Online Shopping}},
  author    = {Yan, Zhao and Duan, Nan and Chen, Peng and Zhou, Ming and Zhou, Jianshe and Li, Zhoujun},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2017},
  pages     = {4618-4626},
  doi       = {10.1609/AAAI.V31I1.11182},
  url       = {https://mlanthology.org/aaai/2017/yan2017aaai-building/}
}