Building Multi-turn Query Interpreters for E-commercial Chatbots with Sparse-to-dense Attentive Modeling.
Yan Fan|Chengyu Wang|Peng He|Yunhua Hu
| Anthology ID: | DBLP:conf/wsdm/Fan0HH22 |
|---|---|
| Volume: | WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21 - 25, 2022 |
| Year: | 2022 |
| Venue: | Web Search and Data Mining (WSDM) |
| Publisher: | ACM |
| Pages: | 1577-1580 |
| URL: | https://doi.org/10.1145/3488560.3502189 |
| DOI: | https://doi.org/10.1145/3488560.3502189 |
| DBLP: | conf/wsdm/Fan0HH22 |
| BibTeX: |
@inproceedings{fan-2022-building,
author = {Yan Fan and
Chengyu Wang and
Peng He and
Yunhua Hu},
editor = {K. Sel\c{c}uk Candan and
Huan Liu and
Leman Akoglu and
Xin Dong and
Jiliang Tang},
title = {{Building Multi-turn Query Interpreters for E-commercial Chatbots with Sparse-to-dense Attentive Modeling}},
booktitle = {{WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21 - 25, 2022}},
pages = {1577--1580},
publisher = {ACM},
year = {2022},
url = {https://doi.org/10.1145/3488560.3502189},
doi = {https://doi.org/10.1145/3488560.3502189}
}