Privacy- and Utility-Preserving Textual Analysis via Calibrated Multivariate Perturbations.
Oluwaseyi Feyisetan|Borja Balle|Thomas Drake|Tom Diethe
| Anthology ID: | DBLP:conf/wsdm/FeyisetanBDD20 |
|---|---|
| Volume: | WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining, Houston, TX, USA, February 3-7, 2020 |
| Year: | 2020 |
| Venue: | Web Search and Data Mining (WSDM) |
| Publisher: | ACM |
| Pages: | 178-186 |
| URL: | https://doi.org/10.1145/3336191.3371856 |
| DOI: | https://doi.org/10.1145/3336191.3371856 |
| DBLP: | conf/wsdm/FeyisetanBDD20 |
| BibTeX: |
@inproceedings{feyisetan-2020-privacy,
author = {Oluwaseyi Feyisetan and
Borja Balle and
Thomas Drake and
Tom Diethe},
editor = {James Caverlee and
Xia Ben Hu and
Mounia Lalmas-Roelleke and
Wei Wang},
title = {{Privacy- and Utility-Preserving Textual Analysis via Calibrated Multivariate Perturbations}},
booktitle = {{WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining, Houston, TX, USA, February 3-7, 2020}},
pages = {178--186},
publisher = {ACM},
year = {2020},
url = {https://doi.org/10.1145/3336191.3371856},
doi = {https://doi.org/10.1145/3336191.3371856}
}