Filters








3 Hits in 3.0 sec

SynTF: Synthetic and Differentially Private Term Frequency Vectors for Privacy-Preserving Text Mining [article]

Benjamin Weggenmann, Florian Kerschbaum
2018 arXiv   pre-print
We therefore propose an automated text anonymization approach that produces synthetic term frequency vectors for the input documents that can be used in lieu of the original vectors.  ...  its term frequencies or related quantities.  ...  ACKNOWLEDGMENTS The authors would like to thank the anonymous referees for their valuable comments and helpful suggestions.  ... 
arXiv:1805.00904v1 fatcat:slzc4vdikfcubfk5qpxnacdco4

ER-AE: Differentially Private Text Generation for Authorship Anonymization [article]

Haohan Bo, Steven H. H. Ding, Benjamin C. M. Fung, Farkhund Iqbal
2021 arXiv   pre-print
Recent studies, such as SynTF, have shown promising results on privacy-preserving text mining.  ...  However, their anonymization algorithm can only output numeric term vectors which are difficult for the recipients to interpret.  ...  Syntf: Synthetic and differentially private term frequency vectors for privacy-preserving text mining.  ... 
arXiv:1907.08736v4 fatcat:av2s6qu5o5dhbmiowmrsve5t6m

ER-AE: Differentially Private Text Generation for Authorship Anonymization

Haohan Bo, Steven H. H. Ding, Benjamin C. M. Fung, Farkhund Iqbal
2021 Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies   unpublished
Recent studies, such as SynTF, have shown promising results on privacy-preserving text mining.  ...  However, their anonymization algorithm can only output numeric term vectors which are difficult for the recipients to interpret.  ...  Syntf: Synthetic and differentially private term frequency vectors for privacy-preserving text mining.  ... 
doi:10.18653/v1/2021.naacl-main.314 fatcat:a5zaessh7vf7tblouixq5oxvam