Published in Proceedings of the Second Workshop on Privacy in NLP, 2020
Online services utilize privacy settings to provide users with control over their data. However, these privacy settings are often hard to locate, causing the user to rely on provider-chosen default values. In this work, we train privacy settings centric encoders and leverage them to create an interface that allows users to search for privacy settings using free-form queries.
Recommended citation: Rishabh Khandelwal, Asmit Nayak*, Yao Yao*, Kassem Fawaz. (2020). "Surfacing Privacy Settings Using Semantic Matching" Proceedings of the Second Workshop on Privacy in NLP. https://www.aclweb.org/anthology/2020.privatenlp-1.4.pdf