Smart devices, such as smart speakers, are becoming ubiquitous, and users expect these devices to act in accordance with their preferences. In particular, since these devices gather and manage personal data, users expect them to adhere to their privacy preferences. However, the current approach of gathering these preferences consists in asking the users directly, which usually triggers automatic responses failing to capture their true preferences. In response, in this paper we present a collaborative filtering approach to predict user preferences as norms. These preference predictions can be readily adopted or can serve to assist users in determining their own preferences. Using a dataset of privacy preferences of smart assistant users, we test the accuracy of our predictions.

翻译：智能设备（如智能音箱）正变得无处不在，用户期望这些设备的行为符合其个人偏好。特别是，由于这些设备收集和管理个人数据，用户期待它们遵循其隐私偏好。然而，当前收集这些偏好的方法通常是直接询问用户，这往往会引发自动化的响应，而无法捕捉其真实偏好。为此，本文提出了一种基于协同过滤的方法，将用户偏好预测为规范。这些偏好预测既可直接采用，也可辅助用户确定自身偏好。我们使用智能助手用户的隐私偏好数据集，对所提预测的准确性进行了测试。