AliMe DA: A Data Augmentation Framework for Question Answering in Cold-start Scenarios.
Guohai Xu|Yan Shao|Chenliang Li|Feng-Lin Li|Bin Bi|Ji Zhang|Haiqing Chen
| Anthology ID: | DBLP:conf/sigir/XuSLLBZC21 |
|---|---|
| Volume: | SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, Virtual Event, Canada, July 11-15, 2021 |
| Year: | 2021 |
| Venue: | Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) |
| Publisher: | ACM |
| Pages: | 2637-2638 |
| URL: | https://doi.org/10.1145/3404835.3464923 |
| DOI: | https://doi.org/10.1145/3404835.3464923 |
| DBLP: | conf/sigir/XuSLLBZC21 |
| BibTeX: |
@inproceedings{xu-2021-alime,
author = {Guohai Xu and
Yan Shao and
Chenliang Li and
Feng-Lin Li and
Bin Bi and
Ji Zhang and
Haiqing Chen},
editor = {Fernando Diaz and
Chirag Shah and
Torsten Suel and
Pablo Castells and
Rosie Jones and
Tetsuya Sakai},
title = {{AliMe DA: A Data Augmentation Framework for Question Answering in Cold-start Scenarios}},
booktitle = {{SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, Virtual Event, Canada, July 11-15, 2021}},
pages = {2637--2638},
publisher = {ACM},
year = {2021},
url = {https://doi.org/10.1145/3404835.3464923},
doi = {https://doi.org/10.1145/3404835.3464923}
}