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pro vyhledávání: '"Weggenmann, Benjamin"'
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. In the field of NLP
Externí odkaz:
http://arxiv.org/abs/2210.13918
As the issues of privacy and trust are receiving increasing attention within the research community, various attempts have been made to anonymize textual data. A significant subset of these approaches incorporate differentially private mechanisms to
Externí odkaz:
http://arxiv.org/abs/2205.02130
Text mining and information retrieval techniques have been developed to assist us with analyzing, organizing and retrieving documents with the help of computers. In many cases, it is desirable that the authors of such documents remain anonymous: Sear
Externí odkaz:
http://arxiv.org/abs/1805.00904
Autor:
Weggenmann, Benjamin, Rublack, Valentin, Andrejczuk, Michael, Mattern, Justus, Kerschbaum, Florian
While vast amounts of personal data are shared daily on public online platformsand used by companies and analysts to gain valuable insights,privacy concerns are also on the rise: Modern authorship attribution techniques have proven effective at ident
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::83bef293693b967f52a49479c02931a9
Publikováno v:
Trusted Systems: 6th International Conference, INTRUST 2014, Beijing, China, December 16-17, 2014, Revised Selected Papers; 2015, p151-167, 17p
