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Differentially Private Language Models for Secure Data Sharing
To protect the privacy of individuals whose data is being shared, it is of high importance to develop methods allowing researchers and companies to release textual data while providing formal privacy guarantees to its originators.
The Limits of Word Level Differential Privacy
As the issues of privacy and trust are receiving increasing attention within the research community, various attempts have been made to anonymize textual data.
SynTF: Synthetic and Differentially Private Term Frequency Vectors for Privacy-Preserving Text Mining
Text mining and information retrieval techniques have been developed to assist us with analyzing, organizing and retrieving documents with the help of computers.
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