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Protecting User Privacy: An Approach for Untraceable Web Browsing History and Unambiguous User Profiles.

, , , , and . WSDM, page 213-221. ACM, (2019)

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Deep Reinforcement Learning-based Text Anonymization against Private-Attribute Inference., , and . EMNLP/IJCNLP (1), page 2360-2369. Association for Computational Linguistics, (2019)Privacy-Aware Recommendation with Private-Attribute Protection using Adversarial Learning., , , , , and . WSDM, page 34-42. ACM, (2020)Signed Link Analysis in Social Media Networks., , and . ICWSM, page 539-542. AAAI Press, (2016)A Study of Reddit-User's Response to Rape., , , , and . ASONAM, page 591-592. IEEE Computer Society, (2018)Privacy Preserving Text Representation Learning., , , , and . HT, page 275-276. ACM, (2019)Securing Social Media User Data: An Adversarial Approach., , , and . HT, page 165-173. ACM, (2018)PPSL: Privacy-Preserving Text Classification for Split Learning., , , and . ICDIS, page 160-167. IEEE, (2022)A Feature-Driven Approach for Identifying Pathogenic Social Media Accounts., , , , , , and . ICDIS, page 26-33. IEEE, (2020)Protecting User Privacy: An Approach for Untraceable Web Browsing History and Unambiguous User Profiles., , , , and . CoRR, (2018)Similar but Different: Exploiting Users' Congruity for Recommendation Systems., and . SBP-BRiMS, volume 10899 of Lecture Notes in Computer Science, page 129-140. Springer, (2018)