Truth Inference at Scale: A Bayesian Model for Adjudicating Highly Redundant Crowd Annotations.
Yuan Li|Benjamin I. P. Rubinstein|Trevor Cohn
| Anthology ID: | DBLP:conf/www/LiRC19 |
|---|---|
| Volume: | The World Wide Web Conference, WWW 2019, San Francisco, CA, USA, May 13-17, 2019 |
| Year: | 2019 |
| Venue: | The Web Conference (WWW) |
| Publisher: | ACM |
| Pages: | 1028-1038 |
| URL: | https://doi.org/10.1145/3308558.3313459 |
| DOI: | https://doi.org/10.1145/3308558.3313459 |
| DBLP: | conf/www/LiRC19 |
| BibTeX: |
@inproceedings{li-2019-truth,
author = {Yuan Li and
Benjamin I. P. Rubinstein and
Trevor Cohn},
editor = {Ling Liu and
Ryen W. White and
Amin Mantrach and
Fabrizio Silvestri and
Julian J. McAuley and
Ricardo Baeza-Yates and
Leila Zia},
title = {{Truth Inference at Scale: A Bayesian Model for Adjudicating Highly Redundant Crowd Annotations}},
booktitle = {{The World Wide Web Conference, WWW 2019, San Francisco, CA, USA, May 13-17, 2019}},
pages = {1028--1038},
publisher = {ACM},
year = {2019},
url = {https://doi.org/10.1145/3308558.3313459},
doi = {https://doi.org/10.1145/3308558.3313459}
}