SynTF: Synthetic and Differentially Private Term Frequency Vectors for Privacy-Preserving Text Mining.

Benjamin Weggenmann|Florian Kerschbaum


Anthology ID:DBLP:conf/sigir/WeggenmannK18
Volume:The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval, SIGIR 2018, Ann Arbor, MI, USA, July 08-12, 2018
Year:2018
Venue:Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)
Publisher:ACM
Pages:305-314
URL:https://doi.org/10.1145/3209978.3210008
DOI:https://doi.org/10.1145/3209978.3210008
DBLP:conf/sigir/WeggenmannK18
BibTeX:
@inproceedings{weggenmann-2018-syntf, author = {Benjamin Weggenmann and Florian Kerschbaum}, editor = {Kevyn Collins-Thompson and Qiaozhu Mei and Brian D. Davison and Yiqun Liu and Emine Yilmaz}, title = {{SynTF: Synthetic and Differentially Private Term Frequency Vectors for Privacy-Preserving Text Mining}}, booktitle = {{The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval, SIGIR 2018, Ann Arbor, MI, USA, July 08-12, 2018}}, pages = {305--314}, publisher = {ACM}, year = {2018}, url = {https://doi.org/10.1145/3209978.3210008}, doi = {https://doi.org/10.1145/3209978.3210008} }