Anonymisation Models for Text Data: State of the art, Challenges and Future Directions

Pierre Lison, Ildikó Pilán, David Sánchez 0001, Montserrat Batet, Lilja Øvrelid. Anonymisation Models for Text Data: State of the art, Challenges and Future Directions. In Chengqing Zong, Fei Xia, Wenjie Li 0002, Roberto Navigli, editors, Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, ACL/IJCNLP 2021, (Volume 1: Long Papers), Virtual Event, August 1-6, 2021. pages 4188-4203, Association for Computational Linguistics, 2021. [doi]

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