Uncertainty-aware Pseudo Label Refinery for Entity Alignment.
| Anthology ID: | DBLP:conf/www/LiS22 |
|---|---|
| Volume: | WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25 - 29, 2022 |
| Year: | 2022 |
| Venue: | The Web Conference (WWW) |
| Publisher: | ACM |
| Pages: | 829-837 |
| URL: | https://doi.org/10.1145/3485447.3511926 |
| DOI: | https://doi.org/10.1145/3485447.3511926 |
| DBLP: | conf/www/LiS22 |
| BibTeX: |
@inproceedings{li-2022-uncertaintyaware,
author = {Jia Li and
Dandan Song},
editor = {Fr\'{e}d\'{e}rique Laforest and
Rapha\"{e}l Troncy and
Elena Simperl and
Deepak Agarwal and
Aristides Gionis and
Ivan Herman and
Lionel M\'{e}dini},
title = {{Uncertainty-aware Pseudo Label Refinery for Entity Alignment}},
booktitle = {{WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25 - 29, 2022}},
pages = {829--837},
publisher = {ACM},
year = {2022},
url = {https://doi.org/10.1145/3485447.3511926},
doi = {https://doi.org/10.1145/3485447.3511926}
}