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Systematizing the State of Knowledge in Detecting Privacy Sensitive Information in Unstructured Texts using Machine Learning., , , and . PST, page 1-7. IEEE, (2023)Evaluating Privacy Policy Summarization: An Experimental Study among Japanese Users., , , and . ICISSP, page 370-377. SciTePress, (2019)Effects of Explanatory Information on Privacy Policy Summarization Tool Perception., , , and . ICISSP (Revised Selected Papers), volume 1545 of Communications in Computer and Information Science, page 156-177. Springer, (2020)User Acceptance Criteria for Privacy Preserving Machine Learning Techniques., , and . ARES, page 149:1-149:8. ACM, (2023)OPA2D: One-Pixel Attack, Detection, and Defense in Deep Neural Networks., , , , , and . IJCNN, page 1-10. IEEE, (2021)User Study of the Effectiveness of a Privacy Policy Summarization Tool., , , and . ICISSP (Revised Selected Papers), volume 1221 of Communications in Computer and Information Science, page 186-206. Springer, (2019)Influence of Errors on the Evaluation of Text Classification Systems., , and . VISIGRAPP (Revised Selected Papers), volume 1815 of Communications in Computer and Information Science, page 161-181. Springer, (2022)The issue of user trust in decentralized applications running on blockchain platforms., and . ISTAS, page 1-4. IEEE, (2017)Comparing Perception of Disclosure of Different Types of Information Related to Automated Tools., and . ICISSP, page 544-550. SCITEPRESS, (2022)Effect of Errors on the Evaluation of Machine Learning Systems., , and . VISIGRAPP (2: HUCAPP), page 48-57. SCITEPRESS, (2022)