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} }